神经网络隐藏层节点数效率最优值
本文通过调节神经网络隐藏层节点数观察隐藏层节点数对神经网络性能的影响，并通过实验找到隐藏层节点数的收敛效率最优值。
首先构造一个二分类网络区分minst数据集的0和2，实验将28*28的图片缩小到9*9，网络用一个3*3的卷积核，网络结构是81*49*n*2，画成图
这个网络由两部分组成，左右两边分别向1,0和0,1收敛，左边输入minst的0，右边输入minst的2，让左右两个网络的权重共享，达到分类的目的。由前面的实验表明这种效果相当于将两个弹性系数为k的弹簧并联成一个弹性系数为2k的弹簧。
这个网络的迭代次数可以用左右两个网络的迭代次数精确的计算，表达式为
具体计算过程请见
0-2《神经网络与振子动力系统---验算实例二分类0，2》2019-2-9
https://blog.csdn.net/georgesale/article/details/86802727
本文尝试了节点数n=20，30，40，50，60，70，80，90，100，200，500，1000共12个值
| 具体进样顺序 |
|||
| n=20 |
|||
| δ=0.5 |
|||
| 初始化权重 |
|||
| 迭代次数 |
|||
| minst 0-1 |
1 |
判断是否达到收敛 |
|
| minst 2-1 |
2 |
判断是否达到收敛 |
|
| 梯度下降 |
|||
| minst 0-2 |
3 |
判断是否达到收敛 |
|
| minst 2-2 |
4 |
判断是否达到收敛 |
|
| 梯度下降 |
|||
| … |
|||
| minst 0-4999 |
9997 |
判断是否达到收敛 |
|
| minst 2-4999 |
9998 |
判断是否达到收敛 |
|
| 梯度下降 |
|||
| … |
|||
| 如果4999图片内没有达到收敛标准再次从头循环 |
|||
| minst 0-1 |
9999 |
判断是否达到收敛 |
|
| minst 2-1 |
10000 |
判断是否达到收敛 |
|
| 梯度下降 |
|||
| … |
|||
| 每当网路达到收敛标准记录迭代次数和对应的准确率测试结果 |
|||
| 将这一过程重复199次 |
|||
| δ=0.4 |
|||
| … |
|||
| δ=1e-6 |
|||
| … |
|||
| n=30 |
|||
| … |
|||
收敛条件是
if (Math.abs(f2[0]-y[0])< δ && Math.abs(f2[1]-y[1])< δ )
δ就是神经网络输出值与目标值的绝对值的差值
本文尝试了δ从0.5到1e-6在内的26个值，训练集是misnt0和2的前4999张图片。
这个网络简写成
S（minst 0）81-（con3*3）49-n-2-（1,0）
S（minst 2）81-（con3*3）49-n-2-（0,1）
w=w，w1=w1,w2=w2
进一步简写成
d2（minst 0,2）81-con（3*3）49-n-2-（2*k） ,k∈(0,1)
测试集中有980个0和1032个0.取199次的平均值得到的数据，共收敛了12*26*199次。
首先观察隐藏层节点数num对网络迭代次数n的影响
| n |
num |
|||||||||||
| δ |
49*20*2 |
49*30*2 |
49*40*2 |
49*50*2 |
49*60*2 |
49*70*2 |
49*80*2 |
49*90*2 |
49*100*2 |
49*200*2 |
49*500*2 |
49*1000*2 |
| 0.5 |
25.54271357 |
19.34673367 |
14.68341709 |
11.38190955 |
9.56281407 |
8.195979899 |
8.67839196 |
6.64321608 |
6.713567839 |
5.874371859 |
366.4924623 |
427.3366834 |
| 0.4 |
1963.994975 |
1847.326633 |
1764.221106 |
1649.487437 |
1576.447236 |
1480.261307 |
1418.326633 |
1433.763819 |
1318.366834 |
972.9296482 |
327.4070352 |
416.7386935 |
| 0.3 |
2327.336683 |
2152.909548 |
2053.512563 |
1929.819095 |
1867.296482 |
1810.663317 |
1733.020101 |
1758.487437 |
1724.547739 |
1385.969849 |
351.1457286 |
495.2914573 |
| 0.2 |
2514.834171 |
2431.105528 |
2247.01005 |
2125.984925 |
2047.809045 |
2066.81407 |
2061.311558 |
1933.638191 |
1919.311558 |
1509.105528 |
445.1105528 |
431.7738693 |
| 0.1 |
2907.417085 |
2785.725 |
2586.346734 |
2471.467337 |
2336.698492 |
2228.251256 |
2266.432161 |
2177.733668 |
2181.517588 |
1814.653266 |
551.9648241 |
538 |
| 0.01 |
3885.19598 |
3620.905 |
3409.336683 |
3290.39196 |
3211.703518 |
3154.075377 |
2935.085427 |
2922.005025 |
2812.743719 |
2409.899497 |
1947.155779 |
958.5577889 |
| 0.001 |
5718.60804 |
4846.435 |
4769.61809 |
4482.884422 |
4176.959799 |
4087.306533 |
4172.447236 |
3935.537688 |
3826.743719 |
3242.41206 |
2687.366834 |
2178.155779 |
| 1.00E-04 |
9210.336683 |
7709.22 |
6843.773869 |
6534.899497 |
6287.417085 |
5992.899497 |
5800.959799 |
5795.190955 |
5498.035176 |
4641.507538 |
3755.718593 |
3671.733668 |
| 9.00E-05 |
9710.065327 |
7951.16 |
7050.683417 |
6653.683417 |
6228.537688 |
6188.085427 |
5818.040201 |
5733.683417 |
5592.457286 |
4643.81407 |
3834.145729 |
3766.914573 |
| 8.00E-05 |
9738.582915 |
8182.51 |
7373.899497 |
6771.175879 |
6455.231156 |
6244.547739 |
6237.20603 |
5827.537688 |
6010.316583 |
4800.718593 |
4004.120603 |
3537.552764 |
| 7.00E-05 |
10116.43216 |
8193.28 |
7534.085427 |
6862.090452 |
6728.658291 |
6499.869347 |
6520.226131 |
5903.482412 |
5896.547739 |
4944.120603 |
3983.703518 |
3755.638191 |
| 6.00E-05 |
11118.71357 |
8780.59 |
7912.809045 |
7370.768844 |
6712.939698 |
6664.39196 |
6259.512563 |
6207.869347 |
5955.120603 |
5034.21608 |
4338.090452 |
3795.145729 |
| 5.00E-05 |
12111.80905 |
9227.095 |
8041.648241 |
7763.61809 |
7220.683417 |
6979.60804 |
6658.964824 |
6452.015075 |
6224.266332 |
5301.120603 |
4155.115578 |
3860.778894 |
| 4.00E-05 |
13728.94472 |
9473.415 |
8914.708543 |
7870.065327 |
7335.974874 |
6974.879397 |
6793.105528 |
6877.788945 |
6384.939698 |
5264.40201 |
4743.256281 |
3863.552764 |
| 3.00E-05 |
15497.58291 |
10478 |
8983.256281 |
8461.718593 |
7950.296482 |
7625.261307 |
7386.211055 |
6936.482412 |
6846.653266 |
5613.075377 |
4725.738693 |
4506.376884 |
| 2.00E-05 |
23317.27638 |
12060.835 |
10254.74874 |
9369.105528 |
8535.261307 |
8129.582915 |
7959.653266 |
7832.623116 |
7559.673367 |
6100.708543 |
5045.266332 |
4465.934673 |
| 1.00E-05 |
38937.0402 |
19757.36 |
13325.50251 |
11380.39196 |
9927.246231 |
10038.44221 |
9422.306533 |
8606.266332 |
8652.512563 |
6956.778894 |
5789.261307 |
4991.507538 |
| 9.00E-06 |
43911.22613 |
22245.54 |
14199.68844 |
12113.8191 |
10543.47739 |
10136.58794 |
9981.849246 |
9199.065327 |
8930.713568 |
7182.894472 |
5733.809045 |
5153.572864 |
| 8.00E-06 |
53602.42714 |
22214.925 |
15274 |
12452.02513 |
10837.76382 |
10599.34673 |
9611.567839 |
9402.351759 |
8958.738693 |
7194.165829 |
5806.984925 |
5193.623116 |
| 7.00E-06 |
53211.27638 |
28045.605 |
16940.78894 |
13635.23618 |
12077.03015 |
11315.09548 |
10070.8392 |
9749.487437 |
9323.19598 |
7430.01005 |
6073.266332 |
5183.844221 |
| 6.00E-06 |
57217.68844 |
28410.335 |
19087.45226 |
14732.50251 |
12292.15578 |
11030.19598 |
10436.59799 |
10225.84925 |
9608.979899 |
7687.753769 |
6300.633166 |
5706.01005 |
| 5.00E-06 |
77478.28141 |
33681.76 |
19354.78392 |
16120.72362 |
12830.23116 |
12153.75377 |
11567.1608 |
10823.58291 |
10396.34171 |
8213.728643 |
6550.331658 |
6091.135678 |
| 4.00E-06 |
84001.1407 |
37281.575 |
24309.84925 |
17517.83417 |
16267.97487 |
14135.48744 |
11897.39196 |
11054.8794 |
11352.55276 |
8421.467337 |
6433.165829 |
5787.120603 |
| 3.00E-06 |
90617.75879 |
45173.585 |
30329.22111 |
20533.78894 |
17320.0201 |
15464.65829 |
14069.67337 |
13135.27638 |
12671.9397 |
8811.065327 |
6982.005025 |
6397.271357 |
| 2.00E-06 |
119310.4422 |
60366.615 |
40249.79397 |
29888.1809 |
24441.90452 |
20569.77889 |
18074.0402 |
15542.84422 |
15187.56784 |
10138.0402 |
7838.643216 |
6485.407035 |
| 1.00E-06 |
153821.392 |
90392.445 |
66962.1608 |
48307.74372 |
40945.17588 |
31941.37186 |
30805.02513 |
25686.16583 |
23370.95477 |
15122.70352 |
9934.658291 |
8098.125628 |
数据表明当δ不变的情况下隐藏层节点数num减小会导致迭代次数n增加。
然后观察num对网络最大性能p-max的影响
P-max等于199次收敛出现的最大准确率
| p-max |
num |
|||||||||||
| δ |
49*20*2 |
49*30*2 |
49*40*2 |
49*50*2 |
49*60*2 |
49*70*2 |
49*80*2 |
49*90*2 |
49*100*2 |
49*200*2 |
49*500*2 |
49*1000*2 |
| 0.5 |
0.809642147 |
0.90805169 |
0.819085487 |
0.887673956 |
0.810636183 |
0.805666004 |
0.840457256 |
0.795228628 |
0.784294235 |
0.798210736 |
0.522365805 |
0.924950298 |
| 0.4 |
0.972166998 |
0.972166998 |
0.972166998 |
0.972166998 |
0.972166998 |
0.967196819 |
0.970178926 |
0.969184891 |
0.971172962 |
0.953777336 |
0.512922465 |
0.863817097 |
| 0.3 |
0.97166998 |
0.969184891 |
0.970178926 |
0.970178926 |
0.970675944 |
0.970675944 |
0.97166998 |
0.974652087 |
0.969681909 |
0.966202783 |
0.505964215 |
0.802186879 |
| 0.2 |
0.977137177 |
0.972664016 |
0.97415507 |
0.973161034 |
0.97415507 |
0.968687873 |
0.970675944 |
0.972166998 |
0.978131213 |
0.965208748 |
0.487077535 |
0.705765408 |
| 0.1 |
0.97415507 |
0.968190855 |
0.977137177 |
0.972664016 |
0.97415507 |
0.974652087 |
0.967693837 |
0.969184891 |
0.972166998 |
0.970178926 |
0.742047714 |
0.792246521 |
| 0.01 |
0.975646123 |
0.972664016 |
0.975646123 |
0.97415507 |
0.975149105 |
0.979622266 |
0.970178926 |
0.970675944 |
0.967196819 |
0.974652087 |
0.965208748 |
0.946819085 |
| 0.001 |
0.975646123 |
0.980119284 |
0.977634195 |
0.976640159 |
0.980119284 |
0.975149105 |
0.975149105 |
0.976640159 |
0.977137177 |
0.972166998 |
0.969681909 |
0.970675944 |
| 1.00E-04 |
0.981610338 |
0.982107356 |
0.978628231 |
0.978131213 |
0.98359841 |
0.976640159 |
0.980119284 |
0.979125249 |
0.981610338 |
0.980119284 |
0.972166998 |
0.979622266 |
| 9.00E-05 |
0.982604374 |
0.978628231 |
0.98359841 |
0.977137177 |
0.982604374 |
0.980616302 |
0.977137177 |
0.979125249 |
0.977137177 |
0.977137177 |
0.975646123 |
0.976143141 |
| 8.00E-05 |
0.979125249 |
0.98359841 |
0.984095427 |
0.98111332 |
0.976143141 |
0.979125249 |
0.977634195 |
0.982604374 |
0.978628231 |
0.98359841 |
0.969681909 |
0.97415507 |
| 7.00E-05 |
0.98111332 |
0.982107356 |
0.981610338 |
0.979622266 |
0.979125249 |
0.980119284 |
0.982107356 |
0.98111332 |
0.977634195 |
0.983101392 |
0.97415507 |
0.976640159 |
| 6.00E-05 |
0.980119284 |
0.981610338 |
0.982604374 |
0.981610338 |
0.978131213 |
0.980616302 |
0.982604374 |
0.979622266 |
0.978628231 |
0.977634195 |
0.976640159 |
0.977634195 |
| 5.00E-05 |
0.98111332 |
0.980616302 |
0.982604374 |
0.981610338 |
0.982604374 |
0.980119284 |
0.980616302 |
0.979125249 |
0.980616302 |
0.979622266 |
0.972664016 |
0.979125249 |
| 4.00E-05 |
0.984095427 |
0.984592445 |
0.98111332 |
0.982107356 |
0.981610338 |
0.982107356 |
0.979622266 |
0.980616302 |
0.977137177 |
0.977634195 |
0.971172962 |
0.970675944 |
| 3.00E-05 |
0.98111332 |
0.981610338 |
0.98111332 |
0.982604374 |
0.980119284 |
0.979622266 |
0.983101392 |
0.978628231 |
0.977137177 |
0.985089463 |
0.977137177 |
0.972166998 |
| 2.00E-05 |
0.982107356 |
0.978131213 |
0.981610338 |
0.983101392 |
0.982107356 |
0.978628231 |
0.98111332 |
0.981610338 |
0.98111332 |
0.977634195 |
0.978628231 |
0.97415507 |
| 1.00E-05 |
0.986580517 |
0.982604374 |
0.984592445 |
0.982107356 |
0.979125249 |
0.980616302 |
0.98111332 |
0.979125249 |
0.98359841 |
0.979125249 |
0.982107356 |
0.973161034 |
| 9.00E-06 |
0.986083499 |
0.98359841 |
0.984095427 |
0.982604374 |
0.982604374 |
0.983101392 |
0.982604374 |
0.98111332 |
0.981610338 |
0.980616302 |
0.977634195 |
0.978131213 |
| 8.00E-06 |
0.984095427 |
0.982604374 |
0.984095427 |
0.983101392 |
0.979622266 |
0.980616302 |
0.980119284 |
0.983101392 |
0.984095427 |
0.983101392 |
0.981610338 |
0.977137177 |
| 7.00E-06 |
0.987574553 |
0.982107356 |
0.981610338 |
0.98359841 |
0.979125249 |
0.979622266 |
0.98111332 |
0.980119284 |
0.984095427 |
0.982107356 |
0.98111332 |
0.980119284 |
| 6.00E-06 |
0.987077535 |
0.984095427 |
0.982604374 |
0.982107356 |
0.984095427 |
0.982107356 |
0.978628231 |
0.981610338 |
0.980616302 |
0.984095427 |
0.979622266 |
0.978131213 |
| 5.00E-06 |
0.985586481 |
0.987574553 |
0.984592445 |
0.982107356 |
0.98359841 |
0.98359841 |
0.981610338 |
0.98111332 |
0.98111332 |
0.977634195 |
0.980119284 |
0.98111332 |
| 4.00E-06 |
0.985089463 |
0.986083499 |
0.98359841 |
0.985586481 |
0.982604374 |
0.985089463 |
0.979622266 |
0.984592445 |
0.984095427 |
0.980119284 |
0.979622266 |
0.978131213 |
| 3.00E-06 |
0.985089463 |
0.986083499 |
0.982604374 |
0.982604374 |
0.984095427 |
0.983101392 |
0.983101392 |
0.984095427 |
0.979622266 |
0.982604374 |
0.982604374 |
0.979125249 |
| 2.00E-06 |
0.986580517 |
0.985586481 |
0.98359841 |
0.986083499 |
0.982107356 |
0.985586481 |
0.985586481 |
0.982604374 |
0.98111332 |
0.982107356 |
0.980119284 |
0.98111332 |
| 1.00E-06 |
0.985586481 |
0.985586481 |
0.985586481 |
0.984592445 |
0.985089463 |
0.986580517 |
0.98359841 |
0.985089463 |
0.984095427 |
0.979622266 |
0.979622266 |
0.983101392 |
数据表明当δ保持不变的情况下，num减小会使p-max增加。
但是比较两组数据
| p-max |
num |
|
|
| δ |
49*20*2 |
49*1000*2 |
p-max的差值 |
| 0.5 |
0.809642147 |
0.924950298 |
-0.11530815 |
| 0.4 |
0.972166998 |
0.863817097 |
0.108349901 |
| 0.3 |
0.97166998 |
0.802186879 |
0.169483101 |
| 0.2 |
0.977137177 |
0.705765408 |
0.271371769 |
| 0.1 |
0.97415507 |
0.792246521 |
0.181908549 |
| 0.01 |
0.975646123 |
0.946819085 |
0.028827038 |
| 0.001 |
0.975646123 |
0.970675944 |
0.004970179 |
| 1.00E-04 |
0.981610338 |
0.979622266 |
0.001988072 |
| 1.00E-05 |
0.986580517 |
0.973161034 |
0.013419483 |
| 1.00E-06 |
0.985586481 |
0.983101392 |
0.002485089 |
可以发现在δ不变的情况下，虽然减小num可以增加p-max，但是这个差值已经非常小。
所以可以近似的认为当δ保持不变并且非常小时，隐藏层节点数num对网络最大性能p-max没有影响。
第三步，观察隐藏层节点数对网络平均性能p-ave的影响
P-ave指收敛199次的准确率的平均值
| p-ave |
num |
|||||||||||
| δ |
49*20*2 |
49*30*2 |
49*40*2 |
49*50*2 |
49*60*2 |
49*70*2 |
49*80*2 |
49*90*2 |
49*100*2 |
49*200*2 |
49*500*2 |
49*1000*2 |
| 0.5 |
0.514066356 |
0.517468056 |
0.505159995 |
0.506568628 |
0.506139045 |
0.503766347 |
0.510582235 |
0.505242415 |
0.501268769 |
0.494575262 |
0.487584543 |
0.517270748 |
| 0.4 |
0.798098345 |
0.758122122 |
0.709771522 |
0.671036595 |
0.68098944 |
0.658159086 |
0.649562425 |
0.687073539 |
0.683759254 |
0.628590268 |
0.487267351 |
0.498626333 |
| 0.3 |
0.867506019 |
0.829560326 |
0.806302886 |
0.80407255 |
0.76114419 |
0.720496119 |
0.704841304 |
0.672844841 |
0.675951827 |
0.615358103 |
0.487172443 |
0.49425807 |
| 0.2 |
0.884527009 |
0.86114469 |
0.863946971 |
0.835482082 |
0.817372149 |
0.80650519 |
0.762944943 |
0.754498137 |
0.75380381 |
0.650374137 |
0.487077535 |
0.488423729 |
| 0.1 |
0.893091202 |
0.87929672 |
0.873270428 |
0.845629739 |
0.857625603 |
0.832135329 |
0.80988691 |
0.798243204 |
0.787630998 |
0.662469904 |
0.492489785 |
0.488656004 |
| 0.01 |
0.877126687 |
0.879878231 |
0.869426656 |
0.851996064 |
0.845604763 |
0.829465419 |
0.824749993 |
0.80450463 |
0.788712449 |
0.684338691 |
0.613986933 |
0.536127457 |
| 0.001 |
0.834448085 |
0.847487575 |
0.844241086 |
0.858786977 |
0.85543273 |
0.855510155 |
0.832802182 |
0.844560776 |
0.851858697 |
0.773122571 |
0.627933405 |
0.580796627 |
| 1.00E-04 |
0.867138875 |
0.854035785 |
0.84394887 |
0.841940817 |
0.843017273 |
0.818820744 |
0.814464969 |
0.827757076 |
0.83437066 |
0.802121942 |
0.74015455 |
0.689735956 |
| 9.00E-05 |
0.860355455 |
0.858675447 |
0.851499046 |
0.833106886 |
0.817706824 |
0.83393858 |
0.832327642 |
0.827180135 |
0.821058573 |
0.806148036 |
0.771506639 |
0.695053298 |
| 8.00E-05 |
0.85389672 |
0.865089463 |
0.844715626 |
0.829215661 |
0.827594733 |
0.824300429 |
0.807626602 |
0.815256701 |
0.817859177 |
0.808585672 |
0.720099004 |
0.703972147 |
| 7.00E-05 |
0.855270388 |
0.872112326 |
0.831473471 |
0.850245262 |
0.820429184 |
0.829098275 |
0.823154041 |
0.819315264 |
0.81102081 |
0.794324505 |
0.748508946 |
0.682770213 |
| 6.00E-05 |
0.87238129 |
0.870482107 |
0.843089703 |
0.836201385 |
0.829308071 |
0.831078853 |
0.813221175 |
0.816552944 |
0.820034566 |
0.807009701 |
0.743708603 |
0.692630648 |
| 5.00E-05 |
0.852410662 |
0.861960736 |
0.864034387 |
0.847415507 |
0.847815119 |
0.839945253 |
0.83120623 |
0.831635813 |
0.816065916 |
0.800583434 |
0.770442671 |
0.723480724 |
| 4.00E-05 |
0.835124929 |
0.875581511 |
0.858816948 |
0.860690131 |
0.842605173 |
0.830729193 |
0.83619639 |
0.812019841 |
0.812544332 |
0.808977792 |
0.739782411 |
0.735733838 |
| 3.00E-05 |
0.851511534 |
0.858576044 |
0.85720601 |
0.858317432 |
0.842225541 |
0.846683717 |
0.837562564 |
0.825189566 |
0.841641108 |
0.789733958 |
0.776549247 |
0.744467866 |
| 2.00E-05 |
0.876497298 |
0.831160537 |
0.84524761 |
0.847910027 |
0.868642417 |
0.8523707 |
0.837522603 |
0.847318101 |
0.838746416 |
0.784109414 |
0.799784209 |
0.741033697 |
| 1.00E-05 |
0.911018812 |
0.852057654 |
0.836665934 |
0.834795249 |
0.848374577 |
0.833316683 |
0.840974255 |
0.850867159 |
0.836461133 |
0.800823201 |
0.78777336 |
0.777658172 |
| 9.00E-06 |
0.91022708 |
0.880181412 |
0.835894183 |
0.827442381 |
0.834785258 |
0.831778175 |
0.82184531 |
0.846818586 |
0.829363018 |
0.803190905 |
0.778157687 |
0.749065906 |
| 8.00E-06 |
0.914855091 |
0.885067097 |
0.847687743 |
0.826780523 |
0.847000909 |
0.835664406 |
0.854778365 |
0.841146588 |
0.831638311 |
0.818181364 |
0.788430223 |
0.756336354 |
| 7.00E-06 |
0.916635863 |
0.882390656 |
0.853734378 |
0.855994685 |
0.82426796 |
0.830819105 |
0.840519696 |
0.848664296 |
0.84380401 |
0.795076276 |
0.769011559 |
0.764026394 |
| 6.00E-06 |
0.923004685 |
0.89694334 |
0.88005135 |
0.84475309 |
0.847507917 |
0.837335285 |
0.846011868 |
0.834438095 |
0.823451252 |
0.820109494 |
0.761471373 |
0.761114219 |
| 5.00E-06 |
0.939688502 |
0.912897614 |
0.867655874 |
0.862578299 |
0.843486818 |
0.823760952 |
0.825099653 |
0.832549927 |
0.852640439 |
0.807841394 |
0.757295423 |
0.761211625 |
| 4.00E-06 |
0.942116147 |
0.90874503 |
0.890089114 |
0.867151363 |
0.843167128 |
0.831795658 |
0.83539217 |
0.821230906 |
0.826705596 |
0.826800504 |
0.786929179 |
0.756253934 |
| 3.00E-06 |
0.950947581 |
0.921826541 |
0.911336004 |
0.883755257 |
0.865662807 |
0.837200416 |
0.858462292 |
0.844648191 |
0.847979959 |
0.808947821 |
0.790405806 |
0.750984045 |
| 2.00E-06 |
0.956657043 |
0.931230119 |
0.911733119 |
0.904502632 |
0.89570117 |
0.879094778 |
0.871681968 |
0.850894632 |
0.861167168 |
0.822145019 |
0.765687283 |
0.776431861 |
| 1.00E-06 |
0.964684256 |
0.951384195 |
0.938067574 |
0.918104439 |
0.928671688 |
0.909282996 |
0.906707993 |
0.901877679 |
0.890114089 |
0.82579398 |
0.802459115 |
0.787905731 |
可以观察到当δ保持不变，隐藏层节点数num减小可以使网络的平均性能明显提升。
所以现在可以概括出，当δ减小或者num减小时可以使网络的平均性能p-ave和最大性能p-max都增加；
当δ保持不变时，num减小，可以使网络平均性能p-ave明显增加，最大性能p-max小幅增加但增幅很小几乎可以认为是定值。
隐藏层节点数num增加会使使网络的迭代次数n减小，n减小收敛时间会减小。但是单次迭代的计算量随着num的增加会增加，也就是网络的收敛时间随着num的增加可能出现一个极小值。
观察num变化对收敛时间的影响
| 收敛时间 t |
num |
|||||||||||
| δ |
49*20*2 |
49*30*2 |
49*40*2 |
49*50*2 |
49*60*2 |
49*70*2 |
49*80*2 |
49*90*2 |
49*100*2 |
49*200*2 |
49*500*2 |
49*1000*2 |
| 0.5 |
2.573683333 |
2.587983333 |
2.560283333 |
3.762816667 |
3.81045 |
3.7496 |
3.293483333 |
2.293066667 |
2.43915 |
3.149983333 |
4.245333333 |
6.588783333 |
| 0.4 |
4.718883333 |
1.285716667 |
4.5664 |
6.112333333 |
6.137766667 |
5.920466667 |
5.158816667 |
3.886866667 |
3.989633333 |
4.583083333 |
4.153583333 |
6.642633333 |
| 0.3 |
5.101033333 |
5.032916667 |
4.908816667 |
6.495083333 |
6.573616667 |
6.3997 |
5.5733 |
4.269966667 |
4.478883333 |
5.188433333 |
4.217333333 |
6.9026 |
| 0.2 |
5.300866667 |
5.331433333 |
5.137566667 |
6.794116667 |
6.802783333 |
6.79825 |
6.0033 |
4.488333333 |
4.7117 |
5.367133333 |
4.407866667 |
6.653833333 |
| 0.1 |
5.73775 |
5.7774675 |
3.613133333 |
7.298466667 |
7.219083333 |
7.020783333 |
6.277933333 |
4.760566667 |
5.02555 |
5.807316667 |
4.6291 |
3.832633333 |
| 0.01 |
6.847683333 |
6.705703 |
6.411616667 |
8.508666667 |
8.553783333 |
8.388766667 |
7.15395 |
3.5328 |
5.861816667 |
6.746966667 |
7.5318 |
8.282833333 |
| 0.001 |
8.927283333 |
8.08969825 |
7.808833333 |
10.24335 |
10.11853333 |
9.76785 |
8.81585 |
6.639583333 |
4.590116667 |
7.963566667 |
9.057166667 |
12.2664 |
| 1.00E-04 |
9.623683333 |
10.54121242 |
10.08653333 |
12.07428333 |
11.16841667 |
12.5628 |
10.97385 |
8.654883333 |
9.456283333 |
9.966366667 |
7.486983333 |
16.3802 |
| 9.00E-05 |
13.3014 |
13.25799358 |
10.38965 |
13.40321667 |
13.16361667 |
8.88765 |
11.0241 |
8.580316667 |
8.9051 |
9.93785 |
12.99125 |
16.6909 |
| 8.00E-05 |
13.37021667 |
13.49888308 |
10.73571667 |
13.52725 |
13.38445 |
8.987766667 |
11.57958333 |
8.898683333 |
9.003716667 |
10.1633 |
14.0255 |
13.9609 |
| 7.00E-05 |
13.73746667 |
13.67785042 |
9.541083333 |
13.66473333 |
13.60885 |
9.088133333 |
11.9464 |
8.965966667 |
8.836116667 |
10.37076667 |
13.99246667 |
16.67863333 |
| 6.00E-05 |
11.76971667 |
12.33176467 |
11.32175 |
14.37535 |
12.524 |
9.262766667 |
9.707733333 |
9.1736 |
9.0771 |
10.55046667 |
14.81258333 |
16.86845 |
| 5.00E-05 |
15.98893333 |
14.89889783 |
11.51181667 |
14.95273333 |
14.49401667 |
8.409216667 |
12.3382 |
7.8246 |
9.30745 |
10.9668 |
10.72143333 |
14.77306667 |
| 4.00E-05 |
17.64821667 |
15.20016725 |
12.61531667 |
15.06871667 |
14.67543333 |
9.587566667 |
12.2635 |
9.7955 |
7.5357 |
10.92735 |
15.775 |
17.06073333 |
| 3.00E-05 |
19.8066 |
16.60980033 |
13.41036667 |
15.92383333 |
15.58015 |
10.27231667 |
13.04498333 |
9.864133333 |
12.65855 |
11.46395 |
15.45998333 |
18.7348 |
| 2.00E-05 |
26.82886667 |
16.90073833 |
17.0075 |
17.20003333 |
16.48243333 |
10.66216667 |
13.83065 |
10.8905 |
13.51236667 |
11.49351667 |
16.13273333 |
18.36801667 |
| 1.00E-05 |
44.47536667 |
26.07639617 |
23.55963333 |
13.92028333 |
14.47121667 |
12.74388333 |
15.77338333 |
11.7895 |
14.78183333 |
12.38198333 |
14.03175 |
18.96983333 |
| 9.00E-06 |
48.72323333 |
31.88737858 |
24.37861667 |
16.80695 |
15.37703333 |
12.68511667 |
16.52786667 |
12.53058333 |
13.23533333 |
12.66046667 |
17.28331667 |
20.49336667 |
| 8.00E-06 |
60.62751667 |
31.84381417 |
24.35431667 |
16.85463333 |
15.79941667 |
14.63876667 |
16.10595 |
14.02375 |
14.5974 |
11.46198333 |
17.40931667 |
20.627 |
| 7.00E-06 |
60.32546667 |
36.42414742 |
28.06098333 |
18.18205 |
14.85106667 |
18.34166667 |
16.66091667 |
13.2736 |
15.29951667 |
13.01591667 |
14.86761667 |
20.61075 |
| 6.00E-06 |
79.54751667 |
38.18907842 |
29.14715 |
18.03356667 |
16.64125 |
17.9834 |
17.17878333 |
13.77916667 |
15.28886667 |
13.79523333 |
18.45381667 |
22.16506667 |
| 5.00E-06 |
106.31895 |
44.85858 |
30.95061667 |
21.0275 |
17.45285 |
17.73143333 |
18.63571667 |
15.09455 |
14.19968333 |
14.91083333 |
19.49863333 |
23.87273333 |
| 4.00E-06 |
117.1161667 |
49.6259235 |
37.7089 |
22.65601667 |
20.26786667 |
22.10036667 |
15.26208333 |
13.82383333 |
17.32203333 |
12.79816667 |
15.8469 |
18.0721 |
| 3.00E-06 |
90.04676667 |
59.95490242 |
45.34965 |
25.43591667 |
22.89251667 |
23.99786667 |
17.37821667 |
17.28726667 |
18.97865 |
15.99893333 |
19.81571667 |
22.57133333 |
| 2.00E-06 |
127.4180833 |
80.98681442 |
59.94623333 |
35.2666 |
29.9583 |
29.68673333 |
21.64041667 |
19.98911667 |
20.99238333 |
17.87105 |
21.9985 |
19.35698333 |
| 1.00E-06 |
191.1962667 |
118.6276478 |
95.7733 |
60.3937 |
51.36656667 |
43.53973333 |
35.84566667 |
28.78283333 |
32.50871667 |
20.03686667 |
23.57898333 |
27.22888333 |
| sum |
1107.077617 |
680.2029096 |
540.8557833 |
427.9822 |
393.3754667 |
349.2147667 |
339.9946333 |
272.8935667 |
296.59365 |
279.5782833 |
342.4246667 |
414.6534667 |
sum曲线
可以明显观察到这个网络d2（minst 0,2）81-con（3*3）49-n-2-（2*k） ,k∈(0,1)
的sum曲线是一个开口向上有一个极小值的曲线。如果考虑当δ非常小并且保持不变网路的最大性能与隐藏层节点数num无关，可以认为这条曲线的极小值就是网络d2（minst 0,2）81-con（3*3）49-n-2-（2*k） ,k∈(0,1)的收敛效率最优值。对应这个网络这个值在90附近。
比较数据
| num |
|||
| δ |
49*20*2 |
49*90*2 |
|
| p-max |
1.00E-06 |
0.985586481 |
0.985089463 |
| p-ave |
1.00E-06 |
0.964684256 |
0.901877679 |
| 收敛时间 t |
1E-06 |
191.1962667 |
28.78283333 |
这组数据可以理解成当网络的隐藏层节点数num=90时，让网络的δ=1e-6在28min内可以收敛199次其中至少有一次的准确率可以达到0.98509，或者也可以理解成让网络的δ=1e-6，可以达到准确率0.98509的概率是5.025‰，需要时间0.14min。
当网络的隐藏层节点数num=20时，让网络的δ=1e-6在191min内可以收敛199次其中至少有一次的准确率可以达到0.98559，或者也可以理解成让网络的δ=1e-6，可以达到准确率0.98559的概率是5.025‰，需要0.96min。
也就是在概率相同的情况下，多花6.64倍的时间将性能的最大值p-max提升1.000504541倍。
当然如果更在意的是网络的性能稳定输出可预期，应该选择num=20，因为num=20的平均性能p-ave=0.964684256要远好于num=90的平均性能p-ave=0.901877679。
关于调参
δ收敛标准
r学习率
x权重分母，(1-99的随机数)/x
num隐藏层节点数量
n迭代次数
p-ave 网络收敛199次的准确率的平均值
p-max网络收敛199次的准确率的最大值
t收敛时间
| δ |
r |
x |
num |
n |
p-ave |
p-max |
t |
| 减小 |
不变 |
不变 |
不变 |
增加 |
增加 |
增加 |
增加 |
| 减小 |
减小 |
不变 |
不变 |
增加 |
增加 |
增加 |
增加 |
| 减小 |
不变 |
减小 |
不变 |
增加 |
增加 |
增加 |
增加 |
| 减小 |
不变 |
不变 |
减小 |
增加 |
增加 |
增加 |
可能有极小值 |
| 减小 |
减小 |
减小 |
减小 |
增加 |
增加 |
增加 |
可能有极小值 |
| 不变 |
减小 |
不变 |
不变 |
增加 |
增加 |
小幅增加，几乎是定值 |
增加 |
| 不变 |
不变 |
减小 |
不变 |
增加 |
增加 |
几乎是定值 |
增加 |
| 不变 |
不变 |
不变 |
减小 |
增加 |
增加 |
几乎是定值 |
开口向上有极小值 |
| 不变 |
减小 |
减小 |
减小 |
增加 |
增加 |
几乎是定值 |
可能有极小值 |
- δ，r，x，num的减小都会使网络的平均性能p-ave和最大性能p-max增加
- 当δ保持不变并且非常小时，虽然r，x，num减小同样会使最大性能p-max增加但是幅度相当小，几乎可以认为当δ保持不变并且非常小时最大性能p-max是定值
- 在网络的平均性能p-ave和收敛时间之间存在一种平衡，若想网络平均性能p-ave稳定就要增加收敛时间，或者希望网络收敛加快就会导致网络平均性能p-ave不稳定。
- 隐藏层节点数num增加会导致迭代次数n减小，n减小会使收敛时间t减小。但num增加会使单次迭代运算量增加导致t增加，所以num增加可能使收敛时间曲线出现一个极小值，使num出现一个效率最优解。
比如这个网络
d2（minst0,3）81-con（3*3）49-30-2-（2*k） ,k∈(0,1)
先让学习率r=1e-3,再次让学习率r=0.1，会导致网络看起来收敛速度快好多，但性能时好时坏。
因为r增大会导致迭代次数n减小，使得网络在更短的时间里可能达到更小的δ，而δ减小导致准确率增加；
r增大也会导致平均性能下降，使网络性能不稳定。
| 实验数据 |
| 学习率 0.1 |
| 权重初始化方式 |
| Random rand1 =new Random(); |
| int ti1=rand1.nextInt(98)+1; |
| int xx=1; |
| if(ti1%2==0) |
| { xx=-1;} |
| tw[a][b]=xx*((double)ti1/x); |
| 第一层第二层和卷积核的权重的初始化的x分别为1000,1000,200 |
关于学习率的数据
《学习率对神经网络迭代次数和准确率的影响以及近似的数学表达式》
https://blog.csdn.net/georgesale/article/details/86650469
关于权重分母的数据
《神经网络调参---权重对网络分类性能的影响》
https://blog.csdn.net/georgesale/article/details/87174178
| 49*20*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.498890848 |
0.500219847 |
25.54271357 |
0.514066356 |
0.5 |
775.8291457 |
154421 |
2.573683333 |
0.809642147 |
| 0.521526812 |
0.478547237 |
1963.994975 |
0.798098345 |
0.4 |
1422.768844 |
283133 |
4.718883333 |
0.972166998 |
| 0.505646388 |
0.494018432 |
2327.336683 |
0.867506019 |
0.3 |
1538 |
306062 |
5.101033333 |
0.97166998 |
| 0.551366307 |
0.449101025 |
2514.834171 |
0.884527009 |
0.2 |
1598.165829 |
318052 |
5.300866667 |
0.977137177 |
| 0.542295708 |
0.45764721 |
2907.417085 |
0.893091202 |
0.1 |
1729.81407 |
344265 |
5.73775 |
0.97415507 |
| 0.541687788 |
0.458321223 |
3885.19598 |
0.877126687 |
0.01 |
2064.628141 |
410861 |
6.847683333 |
0.975646123 |
| 0.648011374 |
0.351987367 |
5718.60804 |
0.834448085 |
0.001 |
2691.643216 |
535637 |
8.927283333 |
0.975646123 |
| 0.477390129 |
0.522609887 |
9210.336683 |
0.867138875 |
1.00E-04 |
2901.613065 |
577421 |
9.623683333 |
0.981610338 |
| 0.50753594 |
0.492464079 |
9710.065327 |
0.860355455 |
9.00E-05 |
4010.39196 |
798084 |
13.3014 |
0.982604374 |
| 0.512560546 |
0.487439528 |
9738.582915 |
0.85389672 |
8.00E-05 |
4031.135678 |
802213 |
13.37021667 |
0.979125249 |
| 0.522612226 |
0.477387757 |
10116.43216 |
0.855270388 |
7.00E-05 |
4141.869347 |
824248 |
13.73746667 |
0.98111332 |
| 0.482414097 |
0.517585861 |
11118.71357 |
0.87238129 |
6.00E-05 |
3548.658291 |
706183 |
11.76971667 |
0.980119284 |
| 0.502512276 |
0.497487728 |
12111.80905 |
0.852410662 |
5.00E-05 |
4820.773869 |
959336 |
15.98893333 |
0.98111332 |
| 0.552760051 |
0.447240032 |
13728.94472 |
0.835124929 |
4.00E-05 |
5321.070352 |
1058893 |
17.64821667 |
0.984095427 |
| 0.547736806 |
0.452263211 |
15497.58291 |
0.851511534 |
3.00E-05 |
5971.603015 |
1188396 |
19.8066 |
0.98111332 |
| 0.532661935 |
0.467338078 |
23317.27638 |
0.876497298 |
2.00E-05 |
8089.105528 |
1609732 |
26.82886667 |
0.982107356 |
| 0.597988214 |
0.402011788 |
38937.0402 |
0.911018812 |
1.00E-05 |
13409.65327 |
2668522 |
44.47536667 |
0.986580517 |
| 0.592963302 |
0.40703669 |
43911.22613 |
0.91022708 |
9.00E-06 |
14690.41709 |
2923394 |
48.72323333 |
0.986083499 |
| 0.638188992 |
0.361811012 |
53602.42714 |
0.914855091 |
8.00E-06 |
18279.63317 |
3637651 |
60.62751667 |
0.984095427 |
| 0.633164116 |
0.366835882 |
53211.27638 |
0.916635863 |
7.00E-06 |
18188.57789 |
3619528 |
60.32546667 |
0.987574553 |
| 0.633164424 |
0.366835575 |
57217.68844 |
0.923004685 |
6.00E-06 |
23984.0804 |
4772851 |
79.54751667 |
0.987077535 |
| 0.733666309 |
0.266333699 |
77478.28141 |
0.939688502 |
5.00E-06 |
32055.96482 |
6379137 |
106.31895 |
0.985586481 |
| 0.618089613 |
0.381910385 |
84001.1407 |
0.942116147 |
4.00E-06 |
35311.39196 |
7026970 |
117.1161667 |
0.985089463 |
| 0.683416116 |
0.316583885 |
90617.75879 |
0.950947581 |
3.00E-06 |
27149.77387 |
5402806 |
90.04676667 |
0.985089463 |
| 0.77386837 |
0.22613163 |
119310.4422 |
0.956657043 |
2.00E-06 |
38417.50754 |
7645085 |
127.4180833 |
0.986580517 |
| 0.748743291 |
0.251256707 |
153821.392 |
0.964684256 |
1.00E-06 |
57647.02513 |
11471776 |
191.1962667 |
0.985586481 |
| 49*30*2 |
|||||||
| 02 |
|||||||
| δ |
f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
耗时ms/次 |
耗时min/199次 |
最大准确率p-max |
| 0.502203904 |
0.498286111 |
19.34673367 |
0.517468056 |
780.2864322 |
155279 |
0.90805169 |
|
| 0.50709037 |
0.493141453 |
1847.326633 |
0.758122122 |
387.638191 |
77143 |
0.972166998 |
|
| 0.549066594 |
0.45100855 |
2152.909548 |
0.829560326 |
1517.457286 |
301975 |
0.969184891 |
|
| 0.558985857 |
0.440507274 |
2431.105528 |
0.86114469 |
1607.447236 |
319886 |
0.972664016 |
|
| 0.1 |
0.570211 |
0.429708 |
2785.725 |
0.87929672 |
1741.95 |
5.7774675 |
0.968190855 |
| 1.00E-02 |
0.52454 |
0.475436 |
3620.905 |
0.879878231 |
2021.82 |
6.705703 |
0.972664016 |
| 1.00E-03 |
0.504974 |
0.495028 |
4846.435 |
0.847487575 |
2439.105 |
8.08969825 |
0.980119284 |
| 1.00E-04 |
0.53999 |
0.46001 |
7709.22 |
0.854035785 |
3178.255 |
10.54121242 |
0.982107356 |
| 9*1e-5 |
0.489998 |
0.510002 |
7951.16 |
0.858675447 |
3997.385 |
13.25799358 |
0.978628231 |
| 8*1e-5 |
0.460005 |
0.539995 |
8182.51 |
0.865089463 |
4070.015 |
13.49888308 |
0.98359841 |
| 7*1e-5 |
0.420008 |
0.579992 |
8193.28 |
0.872112326 |
4123.975 |
13.67785042 |
0.982107356 |
| 6*1e-5 |
0.450004 |
0.549996 |
8780.59 |
0.870482107 |
3718.12 |
12.33176467 |
0.981610338 |
| 5*1e-5 |
0.485001 |
0.514999 |
9227.095 |
0.861960736 |
4492.13 |
14.89889783 |
0.980616302 |
| 4*1e-5 |
0.415004 |
0.584996 |
9473.415 |
0.875581511 |
4582.965 |
15.20016725 |
0.984592445 |
| 3*1e-5 |
0.440003 |
0.559997 |
10478 |
0.858576044 |
5007.98 |
16.60980033 |
0.981610338 |
| 2*1e-5 |
0.554999 |
0.445001 |
12060.835 |
0.831160537 |
5095.7 |
16.90073833 |
0.978131213 |
| 1.00E-05 |
0.599999 |
0.400002 |
19757.36 |
0.852057654 |
7862.23 |
26.07639617 |
0.982604374 |
| 9*1e-6 |
0.49 |
0.51 |
22245.54 |
0.880181412 |
9614.285 |
31.88737858 |
0.98359841 |
| 8*1e-6 |
0.505 |
0.495 |
22214.925 |
0.885067097 |
9601.15 |
31.84381417 |
0.982604374 |
| 7*1e-6 |
0.534999 |
0.465001 |
28045.605 |
0.882390656 |
10982.155 |
36.42414742 |
0.982107356 |
| 6*1e-6 |
0.545 |
0.455 |
28410.335 |
0.89694334 |
11514.295 |
38.18907842 |
0.984095427 |
| 5*1e-6 |
0.55 |
0.45 |
33681.76 |
0.912897614 |
13525.2 |
44.85858 |
0.987574553 |
| 4*1e-6 |
0.584999 |
0.415001 |
37281.575 |
0.90874503 |
14962.59 |
49.6259235 |
0.986083499 |
| 3*1e-6 |
0.555 |
0.445 |
45173.585 |
0.921826541 |
18076.855 |
59.95490242 |
0.986083499 |
| 2*1e-6 |
0.555 |
0.445 |
60366.615 |
0.931230119 |
24418.135 |
80.98681442 |
0.985586481 |
| 1.00E-06 |
0.595 |
0.405 |
90392.445 |
0.951384195 |
35767.13 |
118.6276478 |
0.985586481 |
| 9*1e-7 |
0.615 |
0.385 |
99247.645 |
0.958735089 |
39147.3 |
129.838545 |
0.986580517 |
| 8*1e-7 |
0.595 |
0.405 |
95016.955 |
0.958625746 |
34390.615 |
114.0622064 |
0.985586481 |
| 7*1e-7 |
0.67 |
0.33 |
113411.54 |
0.958459245 |
40221.6 |
133.40164 |
0.989065606 |
| 6*1e-7 |
0.7 |
0.3 |
116304.29 |
0.95749503 |
40844.955 |
135.4691008 |
0.987077535 |
| 5*1e-7 |
0.675 |
0.325 |
129507.275 |
0.962219185 |
45387.82 |
150.5362697 |
0.986083499 |
| 4*1e-7 |
0.63 |
0.37 |
135768.05 |
0.961893638 |
46543.955 |
154.3707841 |
0.986580517 |
| 3*1e-7 |
0.735 |
0.265 |
149701.355 |
0.965775348 |
53110.415 |
176.1495431 |
0.987077535 |
| 2*1e-7 |
0.665 |
0.335 |
155856.775 |
0.967306163 |
54982.34 |
182.3580943 |
0.989562624 |
| 1.00E-07 |
0.72 |
0.28 |
207402.66 |
0.970795229 |
72608.73 |
240.8189545 |
0.990059642 |
| 1.00E-08 |
0.74 |
0.26 |
369805.81 |
0.975626243 |
129173.65 |
428.4259226 |
0.99055666 |
| 49*40*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.50136909 |
0.497610605 |
14.68341709 |
0.505159995 |
0.5 |
771.9447236 |
153617 |
2.560283333 |
0.819085487 |
| 0.515754395 |
0.484439209 |
1764.221106 |
0.709771522 |
0.4 |
1376.80402 |
273984 |
4.5664 |
0.972166998 |
| 0.536336247 |
0.463992092 |
2053.512563 |
0.806302886 |
0.3 |
1480.045226 |
294529 |
4.908816667 |
0.970178926 |
| 0.521599468 |
0.478828006 |
2247.01005 |
0.863946971 |
0.2 |
1549.015075 |
308254 |
5.137566667 |
0.97415507 |
| 0.52992757 |
0.470136402 |
2586.346734 |
0.873270428 |
0.1 |
1089.386935 |
216788 |
3.613133333 |
0.977137177 |
| 0.522169552 |
0.477820587 |
3409.336683 |
0.869426656 |
0.01 |
1933.070352 |
384697 |
6.411616667 |
0.975646123 |
| 0.472394399 |
0.52760742 |
4769.61809 |
0.844241086 |
0.001 |
2354.422111 |
468530 |
7.808833333 |
0.977634195 |
| 0.547728366 |
0.452271571 |
6843.773869 |
0.84394887 |
1.00E-04 |
3041.165829 |
605192 |
10.08653333 |
0.978628231 |
| 0.482411946 |
0.517588022 |
7050.683417 |
0.851499046 |
9.00E-05 |
3132.557789 |
623379 |
10.38965 |
0.98359841 |
| 0.532657678 |
0.467342217 |
7373.899497 |
0.844715626 |
8.00E-05 |
3236.899497 |
644143 |
10.73571667 |
0.984095427 |
| 0.517586148 |
0.482413781 |
7534.085427 |
0.831473471 |
7.00E-05 |
2876.552764 |
572465 |
9.541083333 |
0.981610338 |
| 0.477387139 |
0.522612929 |
7912.809045 |
0.843089703 |
6.00E-05 |
3413.592965 |
679305 |
11.32175 |
0.982604374 |
| 0.391966541 |
0.6080334 |
8041.648241 |
0.864034387 |
5.00E-05 |
3470.894472 |
690709 |
11.51181667 |
0.982604374 |
| 0.447239611 |
0.552760375 |
8914.708543 |
0.858816948 |
4.00E-05 |
3803.613065 |
756919 |
12.61531667 |
0.98111332 |
| 0.402014831 |
0.597985201 |
8983.256281 |
0.85720601 |
3.00E-05 |
4043.321608 |
804622 |
13.41036667 |
0.98111332 |
| 0.477387991 |
0.522611986 |
10254.74874 |
0.84524761 |
2.00E-05 |
5127.879397 |
1020450 |
17.0075 |
0.981610338 |
| 0.567838226 |
0.432161783 |
13325.50251 |
0.836665934 |
1.00E-05 |
7103.40201 |
1413578 |
23.55963333 |
0.984592445 |
| 0.552763405 |
0.447236594 |
14199.68844 |
0.835894183 |
9.00E-06 |
7350.331658 |
1462717 |
24.37861667 |
0.984095427 |
| 0.54271281 |
0.45728719 |
15274 |
0.847687743 |
8.00E-06 |
7343.005025 |
1461259 |
24.35431667 |
0.984095427 |
| 0.54773822 |
0.452261778 |
16940.78894 |
0.853734378 |
7.00E-06 |
8460.592965 |
1683659 |
28.06098333 |
0.981610338 |
| 0.487437333 |
0.51256267 |
19087.45226 |
0.88005135 |
6.00E-06 |
8788.085427 |
1748829 |
29.14715 |
0.982604374 |
| 0.522612824 |
0.477387173 |
19354.78392 |
0.867655874 |
5.00E-06 |
9331.844221 |
1857037 |
30.95061667 |
0.984592445 |
| 0.442211324 |
0.557788675 |
24309.84925 |
0.890089114 |
4.00E-06 |
11369.47236 |
2262534 |
37.7089 |
0.98359841 |
| 0.417085793 |
0.582914206 |
30329.22111 |
0.911336004 |
3.00E-06 |
13673.22111 |
2720979 |
45.34965 |
0.982604374 |
| 0.537688284 |
0.462311716 |
40249.79397 |
0.911733119 |
2.00E-06 |
18074.16583 |
3596774 |
59.94623333 |
0.98359841 |
| 0.59296466 |
0.407035339 |
66962.1608 |
0.938067574 |
1.00E-06 |
28876.37186 |
5746398 |
95.7733 |
0.985586481 |
| 49*50*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.503227219 |
0.494342336 |
11.38190955 |
0.506568628 |
0.5 |
1134.432161 |
225769 |
3.762816667 |
0.887673956 |
| 0.524651664 |
0.475167917 |
1649.487437 |
0.671036595 |
0.4 |
1842.834171 |
366740 |
6.112333333 |
0.972166998 |
| 0.508473686 |
0.491939885 |
1929.819095 |
0.80407255 |
0.3 |
1958.316583 |
389705 |
6.495083333 |
0.970178926 |
| 0.580215768 |
0.419699433 |
2125.984925 |
0.835482082 |
0.2 |
2048.477387 |
407647 |
6.794116667 |
0.973161034 |
| 0.585428711 |
0.414754365 |
2471.467337 |
0.845629739 |
0.1 |
2200.542714 |
437908 |
7.298466667 |
0.972664016 |
| 0.531897551 |
0.468074368 |
3290.39196 |
0.851996064 |
0.01 |
2565.427136 |
510520 |
8.508666667 |
0.97415507 |
| 0.412148737 |
0.587851395 |
4482.884422 |
0.858786977 |
0.001 |
3088.422111 |
614601 |
10.24335 |
0.976640159 |
| 0.487437047 |
0.512562933 |
6534.899497 |
0.841940817 |
1.00E-04 |
3640.462312 |
724457 |
12.07428333 |
0.978131213 |
| 0.547732516 |
0.452267271 |
6653.683417 |
0.833106886 |
9.00E-05 |
4041.160804 |
804193 |
13.40321667 |
0.977137177 |
| 0.522609159 |
0.477390823 |
6771.175879 |
0.829215661 |
8.00E-05 |
4078.507538 |
811635 |
13.52725 |
0.98111332 |
| 0.472363114 |
0.527636906 |
6862.090452 |
0.850245262 |
7.00E-05 |
4119.98995 |
819884 |
13.66473333 |
0.979622266 |
| 0.517584995 |
0.482414874 |
7370.768844 |
0.836201385 |
6.00E-05 |
4334.246231 |
862521 |
14.37535 |
0.981610338 |
| 0.462313319 |
0.537686706 |
7763.61809 |
0.847415507 |
5.00E-05 |
4508.326633 |
897164 |
14.95273333 |
0.981610338 |
| 0.457287367 |
0.5427126 |
7870.065327 |
0.860690131 |
4.00E-05 |
4543.296482 |
904123 |
15.06871667 |
0.982107356 |
| 0.361814876 |
0.638185101 |
8461.718593 |
0.858317432 |
3.00E-05 |
4801.115578 |
955430 |
15.92383333 |
0.982604374 |
| 0.462312838 |
0.53768715 |
9369.105528 |
0.847910027 |
2.00E-05 |
5185.914573 |
1032002 |
17.20003333 |
0.983101392 |
| 0.482412626 |
0.517587359 |
11380.39196 |
0.834795249 |
1.00E-05 |
4197.070352 |
835217 |
13.92028333 |
0.982107356 |
| 0.582913374 |
0.417086623 |
12113.8191 |
0.827442381 |
9.00E-06 |
5067.341709 |
1008417 |
16.80695 |
0.982604374 |
| 0.517587777 |
0.48241223 |
12452.02513 |
0.826780523 |
8.00E-06 |
5081.798995 |
1011278 |
16.85463333 |
0.983101392 |
| 0.482412149 |
0.517587852 |
13635.23618 |
0.855994685 |
7.00E-06 |
5481.859296 |
1090923 |
18.18205 |
0.98359841 |
| 0.482412158 |
0.517587846 |
14732.50251 |
0.84475309 |
6.00E-06 |
5437.256281 |
1082014 |
18.03356667 |
0.982107356 |
| 0.432161254 |
0.567838747 |
16120.72362 |
0.862578299 |
5.00E-06 |
6339.869347 |
1261650 |
21.0275 |
0.982107356 |
| 0.467336917 |
0.532663083 |
17517.83417 |
0.867151363 |
4.00E-06 |
6830.954774 |
1359361 |
22.65601667 |
0.985586481 |
| 0.422110849 |
0.577889152 |
20533.78894 |
0.883755257 |
3.00E-06 |
7669.120603 |
1526155 |
25.43591667 |
0.982604374 |
| 0.462311648 |
0.537688351 |
29888.1809 |
0.904502632 |
2.00E-06 |
10633.14573 |
2115996 |
35.2666 |
0.986083499 |
| 0.597989769 |
0.402010232 |
48307.74372 |
0.918104439 |
1.00E-06 |
18209.15578 |
3623622 |
60.3937 |
0.984592445 |
| 49*60*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.499448744 |
0.498475215 |
9.56281407 |
0.506139045 |
0.5 |
1148.879397 |
228627 |
3.81045 |
0.810636183 |
| 0.515422279 |
0.484989799 |
1576.447236 |
0.68098944 |
0.4 |
1850.507538 |
368266 |
6.137766667 |
0.972166998 |
| 0.526260757 |
0.473793045 |
1867.296482 |
0.76114419 |
0.3 |
1981.994975 |
394417 |
6.573616667 |
0.970675944 |
| 0.559748895 |
0.440162534 |
2047.809045 |
0.817372149 |
0.2 |
2051.090452 |
408167 |
6.802783333 |
0.97415507 |
| 0.497111091 |
0.502933122 |
2336.698492 |
0.857625603 |
0.1 |
2176.60804 |
433145 |
7.219083333 |
0.97415507 |
| 0.586565838 |
0.413431079 |
3211.703518 |
0.845604763 |
0.01 |
2578.954774 |
513227 |
8.553783333 |
0.975149105 |
| 0.407142331 |
0.592857752 |
4176.959799 |
0.85543273 |
0.001 |
3050.738693 |
607112 |
10.11853333 |
0.980119284 |
| 0.482412875 |
0.51758713 |
6287.417085 |
0.843017273 |
1.00E-04 |
3367.361809 |
670105 |
11.16841667 |
0.98359841 |
| 0.618074689 |
0.381925353 |
6228.537688 |
0.817706824 |
9.00E-05 |
3968.929648 |
789817 |
13.16361667 |
0.982604374 |
| 0.557781216 |
0.442218705 |
6455.231156 |
0.827594733 |
8.00E-05 |
4035.492462 |
803067 |
13.38445 |
0.976143141 |
| 0.577880606 |
0.422119489 |
6728.658291 |
0.820429184 |
7.00E-05 |
4103.150754 |
816531 |
13.60885 |
0.979125249 |
| 0.52763429 |
0.472365675 |
6712.939698 |
0.829308071 |
6.00E-05 |
3776.065327 |
751440 |
12.524 |
0.978131213 |
| 0.452265165 |
0.547734881 |
7220.683417 |
0.847815119 |
5.00E-05 |
4370.035176 |
869641 |
14.49401667 |
0.982604374 |
| 0.507536242 |
0.492463745 |
7335.974874 |
0.842605173 |
4.00E-05 |
4424.723618 |
880526 |
14.67543333 |
0.981610338 |
| 0.487437146 |
0.512562844 |
7950.296482 |
0.842225541 |
3.00E-05 |
4697.507538 |
934809 |
15.58015 |
0.980119284 |
| 0.427137125 |
0.572862854 |
8535.261307 |
0.868642417 |
2.00E-05 |
4969.557789 |
988946 |
16.48243333 |
0.982107356 |
| 0.422111976 |
0.577888029 |
9927.246231 |
0.848374577 |
1.00E-05 |
4363.090452 |
868273 |
14.47121667 |
0.979125249 |
| 0.482412321 |
0.517587672 |
10543.47739 |
0.834785258 |
9.00E-06 |
4636.291457 |
922622 |
15.37703333 |
0.982604374 |
| 0.447236824 |
0.552763173 |
10837.76382 |
0.847000909 |
8.00E-06 |
4763.60804 |
947965 |
15.79941667 |
0.979622266 |
| 0.527638067 |
0.472361931 |
12077.03015 |
0.82426796 |
7.00E-06 |
4477.708543 |
891064 |
14.85106667 |
0.979125249 |
| 0.477387075 |
0.522612927 |
12292.15578 |
0.847507917 |
6.00E-06 |
5017.457286 |
998475 |
16.64125 |
0.984095427 |
| 0.482412217 |
0.517587785 |
12830.23116 |
0.843486818 |
5.00E-06 |
5262.090452 |
1047171 |
17.45285 |
0.98359841 |
| 0.537688152 |
0.462311846 |
16267.97487 |
0.843167128 |
4.00E-06 |
6110.909548 |
1216072 |
20.26786667 |
0.982604374 |
| 0.54271335 |
0.457286652 |
17320.0201 |
0.865662807 |
3.00E-06 |
6902.266332 |
1373551 |
22.89251667 |
0.984095427 |
| 0.447236303 |
0.552763696 |
24441.90452 |
0.89570117 |
2.00E-06 |
9032.648241 |
1797498 |
29.9583 |
0.982107356 |
| 0.422110663 |
0.577889337 |
40945.17588 |
0.928671688 |
1.00E-06 |
15487.39698 |
3081994 |
51.36656667 |
0.985089463 |
| 49*70*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.496656166 |
0.499270269 |
8.195979899 |
0.503766347 |
0.5 |
1130.497487 |
224976 |
3.7496 |
0.805666004 |
| 0.524106159 |
0.475826451 |
1480.261307 |
0.658159086 |
0.4 |
1785.015075 |
355228 |
5.920466667 |
0.967196819 |
| 0.554980563 |
0.445067275 |
1810.663317 |
0.720496119 |
0.3 |
1929.537688 |
383982 |
6.3997 |
0.970675944 |
| 0.50784001 |
0.492109975 |
2066.81407 |
0.80650519 |
0.2 |
2049.678392 |
407895 |
6.79825 |
0.968687873 |
| 0.601647421 |
0.398341678 |
2228.251256 |
0.832135329 |
0.1 |
2116.80402 |
421247 |
7.020783333 |
0.974652087 |
| 0.606292005 |
0.393706481 |
3154.075377 |
0.829465419 |
0.01 |
2529.251256 |
503326 |
8.388766667 |
0.979622266 |
| 0.442244869 |
0.557757091 |
4087.306533 |
0.855510155 |
0.001 |
2945.055276 |
586071 |
9.76785 |
0.975149105 |
| 0.537683184 |
0.462316833 |
5992.899497 |
0.818820744 |
1.00E-04 |
3787.743719 |
753768 |
12.5628 |
0.976640159 |
| 0.517584798 |
0.482415075 |
6188.085427 |
0.83393858 |
9.00E-05 |
2679.693467 |
533259 |
8.88765 |
0.980616302 |
| 0.557781186 |
0.44221886 |
6244.547739 |
0.824300429 |
8.00E-05 |
2709.879397 |
539266 |
8.987766667 |
0.979125249 |
| 0.562807722 |
0.43719234 |
6499.869347 |
0.829098275 |
7.00E-05 |
2740.060302 |
545288 |
9.088133333 |
0.980119284 |
| 0.532659135 |
0.467340824 |
6664.39196 |
0.831078853 |
6.00E-05 |
2792.79397 |
555766 |
9.262766667 |
0.980616302 |
| 0.48241106 |
0.517588972 |
6979.60804 |
0.839945253 |
5.00E-05 |
2535.437186 |
504553 |
8.409216667 |
0.980119284 |
| 0.537686434 |
0.462313542 |
6974.879397 |
0.830729193 |
4.00E-05 |
2890.723618 |
575254 |
9.587566667 |
0.982107356 |
| 0.437187674 |
0.562812327 |
7625.261307 |
0.846683717 |
3.00E-05 |
3097.180905 |
616339 |
10.27231667 |
0.979622266 |
| 0.447237029 |
0.552762998 |
8129.582915 |
0.8523707 |
2.00E-05 |
3214.723618 |
639730 |
10.66216667 |
0.978628231 |
| 0.442211791 |
0.557788219 |
10038.44221 |
0.833316683 |
1.00E-05 |
3842.376884 |
764633 |
12.74388333 |
0.980616302 |
| 0.477387166 |
0.52261283 |
10136.58794 |
0.831778175 |
9.00E-06 |
3824.623116 |
761107 |
12.68511667 |
0.983101392 |
| 0.442211802 |
0.557788194 |
10599.34673 |
0.835664406 |
8.00E-06 |
4413.693467 |
878326 |
14.63876667 |
0.980616302 |
| 0.51256275 |
0.487437249 |
11315.09548 |
0.830819105 |
7.00E-06 |
5530.070352 |
1100500 |
18.34166667 |
0.979622266 |
| 0.407036008 |
0.592963985 |
11030.19598 |
0.837335285 |
6.00E-06 |
5421.974874 |
1079004 |
17.9834 |
0.982107356 |
| 0.477387063 |
0.522612937 |
12153.75377 |
0.823760952 |
5.00E-06 |
5346.085427 |
1063886 |
17.73143333 |
0.98359841 |
| 0.552763486 |
0.447236513 |
14135.48744 |
0.831795658 |
4.00E-06 |
6663.427136 |
1326022 |
22.10036667 |
0.985089463 |
| 0.517587829 |
0.482412173 |
15464.65829 |
0.837200416 |
3.00E-06 |
7235.452261 |
1439872 |
23.99786667 |
0.983101392 |
| 0.462311655 |
0.537688345 |
20569.77889 |
0.879094778 |
2.00E-06 |
8950.768844 |
1781204 |
29.68673333 |
0.985586481 |
| 0.427135761 |
0.572864238 |
31941.37186 |
0.909282996 |
1.00E-06 |
13127.55276 |
2612384 |
43.53973333 |
0.986580517 |
| 49*80*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.494518912 |
0.498554414 |
8.67839196 |
0.510582235 |
0.5 |
993.0100503 |
197609 |
3.293483333 |
0.840457256 |
| 0.526691848 |
0.473599984 |
1418.326633 |
0.649562425 |
0.4 |
1555.422111 |
309529 |
5.158816667 |
0.970178926 |
| 0.550636528 |
0.448957816 |
1733.020101 |
0.704841304 |
0.3 |
1680.39196 |
334398 |
5.5733 |
0.97166998 |
| 0.600441276 |
0.399591492 |
2061.311558 |
0.762944943 |
0.2 |
1809.959799 |
360198 |
6.0033 |
0.970675944 |
| 0.593487253 |
0.406374319 |
2266.432161 |
0.80988691 |
0.1 |
1892.844221 |
376676 |
6.277933333 |
0.967693837 |
| 0.591369001 |
0.408643303 |
2935.085427 |
0.824749993 |
0.01 |
2156.969849 |
429237 |
7.15395 |
0.970178926 |
| 0.477379018 |
0.522623225 |
4172.447236 |
0.832802182 |
0.001 |
2658.045226 |
528951 |
8.81585 |
0.975149105 |
| 0.51758416 |
0.482415753 |
5800.959799 |
0.814464969 |
1.00E-04 |
3308.623116 |
658431 |
10.97385 |
0.980119284 |
| 0.532658333 |
0.467341733 |
5818.040201 |
0.832327642 |
9.00E-05 |
3323.849246 |
661446 |
11.0241 |
0.977137177 |
| 0.562807805 |
0.437192255 |
6237.20603 |
0.807626602 |
8.00E-05 |
3491.331658 |
694775 |
11.57958333 |
0.977634195 |
| 0.557782659 |
0.442217425 |
6520.226131 |
0.823154041 |
7.00E-05 |
3601.929648 |
716784 |
11.9464 |
0.982107356 |
| 0.557784687 |
0.442215324 |
6259.512563 |
0.813221175 |
6.00E-05 |
2926.954774 |
582464 |
9.707733333 |
0.982604374 |
| 0.512561668 |
0.487438398 |
6658.964824 |
0.83120623 |
5.00E-05 |
3719.974874 |
740292 |
12.3382 |
0.980616302 |
| 0.492461943 |
0.507538065 |
6793.105528 |
0.83619639 |
4.00E-05 |
3697.517588 |
735810 |
12.2635 |
0.979622266 |
| 0.47236186 |
0.527638132 |
7386.211055 |
0.837562564 |
3.00E-05 |
3933.140704 |
782699 |
13.04498333 |
0.983101392 |
| 0.467337169 |
0.532662832 |
7959.653266 |
0.837522603 |
2.00E-05 |
4170.01005 |
829839 |
13.83065 |
0.98111332 |
| 0.457287116 |
0.542712887 |
9422.306533 |
0.840974255 |
1.00E-05 |
4755.773869 |
946403 |
15.77338333 |
0.98111332 |
| 0.472362133 |
0.527637872 |
9981.849246 |
0.82184531 |
9.00E-06 |
4983.246231 |
991672 |
16.52786667 |
0.982604374 |
| 0.41206148 |
0.587938516 |
9611.567839 |
0.854778365 |
8.00E-06 |
4856.035176 |
966357 |
16.10595 |
0.980119284 |
| 0.407036269 |
0.592963729 |
10070.8392 |
0.840519696 |
7.00E-06 |
5023.361809 |
999655 |
16.66091667 |
0.98111332 |
| 0.417086149 |
0.582913848 |
10436.59799 |
0.846011868 |
6.00E-06 |
5179.502513 |
1030727 |
17.17878333 |
0.978628231 |
| 0.497487488 |
0.502512514 |
11567.1608 |
0.825099653 |
5.00E-06 |
5618.788945 |
1118143 |
18.63571667 |
0.981610338 |
| 0.467336823 |
0.532663174 |
11897.39196 |
0.83539217 |
4.00E-06 |
4601.557789 |
915725 |
15.26208333 |
0.979622266 |
| 0.427135949 |
0.572864049 |
14069.67337 |
0.858462292 |
3.00E-06 |
5239.663317 |
1042693 |
17.37821667 |
0.983101392 |
| 0.351759182 |
0.64824082 |
18074.0402 |
0.871681968 |
2.00E-06 |
6524.668342 |
1298425 |
21.64041667 |
0.985586481 |
| 0.472361828 |
0.527638172 |
30805.02513 |
0.906707993 |
1.00E-06 |
10807.73869 |
2150740 |
35.84566667 |
0.98359841 |
| 49*90*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.504582017 |
0.500062398 |
6.64321608 |
0.505242415 |
0.5 |
691.3768844 |
137584 |
2.293066667 |
0.795228628 |
| 0.505208465 |
0.494360332 |
1433.763819 |
0.687073539 |
0.4 |
1171.839196 |
233212 |
3.886866667 |
0.969184891 |
| 0.564436653 |
0.435554096 |
1758.487437 |
0.672844841 |
0.3 |
1287.41206 |
256198 |
4.269966667 |
0.974652087 |
| 0.583009041 |
0.417016602 |
1933.638191 |
0.754498137 |
0.2 |
1353.266332 |
269300 |
4.488333333 |
0.972166998 |
| 0.607398168 |
0.392827076 |
2177.733668 |
0.798243204 |
0.1 |
1435.266332 |
285634 |
4.760566667 |
0.969184891 |
| 0.606400697 |
0.393610875 |
2922.005025 |
0.80450463 |
0.01 |
1065.070352 |
211968 |
3.5328 |
0.970675944 |
| 0.392062368 |
0.607939044 |
3935.537688 |
0.844560776 |
0.001 |
2001.80402 |
398375 |
6.639583333 |
0.976640159 |
| 0.50753521 |
0.492464656 |
5795.190955 |
0.827757076 |
1.00E-04 |
2609.512563 |
519293 |
8.654883333 |
0.979125249 |
| 0.567829425 |
0.432170579 |
5733.683417 |
0.827180135 |
9.00E-05 |
2587.030151 |
514819 |
8.580316667 |
0.979125249 |
| 0.552757109 |
0.447242877 |
5827.537688 |
0.815256701 |
8.00E-05 |
2683.01005 |
533921 |
8.898683333 |
0.982604374 |
| 0.487437486 |
0.512562542 |
5903.482412 |
0.819315264 |
7.00E-05 |
2703.306533 |
537958 |
8.965966667 |
0.98111332 |
| 0.552758629 |
0.447241346 |
6207.869347 |
0.816552944 |
6.00E-05 |
2765.834171 |
550416 |
9.1736 |
0.979622266 |
| 0.497487981 |
0.502512061 |
6452.015075 |
0.831635813 |
5.00E-05 |
2359.175879 |
469476 |
7.8246 |
0.979125249 |
| 0.552761672 |
0.44723832 |
6877.788945 |
0.812019841 |
4.00E-05 |
2953.417085 |
587730 |
9.7955 |
0.980616302 |
| 0.512561863 |
0.487438161 |
6936.482412 |
0.825189566 |
3.00E-05 |
2974.110553 |
591848 |
9.864133333 |
0.978628231 |
| 0.422112213 |
0.577887801 |
7832.623116 |
0.847318101 |
2.00E-05 |
3283.487437 |
653430 |
10.8905 |
0.981610338 |
| 0.417086592 |
0.582913408 |
8606.266332 |
0.850867159 |
1.00E-05 |
3554.532663 |
707370 |
11.7895 |
0.979125249 |
| 0.45226195 |
0.547738045 |
9199.065327 |
0.846818586 |
9.00E-06 |
3778.020101 |
751835 |
12.53058333 |
0.98111332 |
| 0.442211577 |
0.55778842 |
9402.351759 |
0.841146588 |
8.00E-06 |
4228.180905 |
841425 |
14.02375 |
0.983101392 |
| 0.391960933 |
0.608039066 |
9749.487437 |
0.848664296 |
7.00E-06 |
4002 |
796416 |
13.2736 |
0.980119284 |
| 0.472362341 |
0.527637657 |
10225.84925 |
0.834438095 |
6.00E-06 |
4154.522613 |
826750 |
13.77916667 |
0.981610338 |
| 0.447236646 |
0.552763351 |
10823.58291 |
0.832549927 |
5.00E-06 |
4551.115578 |
905673 |
15.09455 |
0.98111332 |
| 0.4974874 |
0.502512601 |
11054.8794 |
0.821230906 |
4.00E-06 |
4167.909548 |
829430 |
13.82383333 |
0.984592445 |
| 0.472361923 |
0.527638077 |
13135.27638 |
0.844648191 |
3.00E-06 |
5212.241206 |
1037236 |
17.28726667 |
0.984095427 |
| 0.492462274 |
0.507537726 |
15542.84422 |
0.850894632 |
2.00E-06 |
6026.869347 |
1199347 |
19.98911667 |
0.982604374 |
| 0.437185995 |
0.562814005 |
25686.16583 |
0.901877679 |
1.00E-06 |
8678.201005 |
1726970 |
28.78283333 |
0.985089463 |
| 49*100*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.498643357 |
0.496829735 |
6.713567839 |
0.501268769 |
0.5 |
735.3065327 |
146349 |
2.43915 |
0.784294235 |
| 0.512246234 |
0.488305956 |
1318.366834 |
0.683759254 |
0.4 |
1202.824121 |
239378 |
3.989633333 |
0.971172962 |
| 0.550130787 |
0.450219495 |
1724.547739 |
0.675951827 |
0.3 |
1350.376884 |
268733 |
4.478883333 |
0.969681909 |
| 0.536529857 |
0.463664524 |
1919.311558 |
0.75380381 |
0.2 |
1420.613065 |
282702 |
4.7117 |
0.978131213 |
| 0.576319776 |
0.423707893 |
2181.517588 |
0.787630998 |
0.1 |
1515.241206 |
301533 |
5.02555 |
0.972166998 |
| 0.631382588 |
0.368601263 |
2812.743719 |
0.788712449 |
0.01 |
1767.346734 |
351709 |
5.861816667 |
0.967196819 |
| 0.472351376 |
0.527648682 |
3826.743719 |
0.851858697 |
0.001 |
1383.939698 |
275407 |
4.590116667 |
0.977137177 |
| 0.487436398 |
0.512563697 |
5498.035176 |
0.83437066 |
1.00E-04 |
2851.135678 |
567377 |
9.456283333 |
0.981610338 |
| 0.517585537 |
0.4824144 |
5592.457286 |
0.821058573 |
9.00E-05 |
2684.954774 |
534306 |
8.9051 |
0.977137177 |
| 0.557780426 |
0.442219548 |
6010.316583 |
0.817859177 |
8.00E-05 |
2714.688442 |
540223 |
9.003716667 |
0.978628231 |
| 0.557783228 |
0.442216773 |
5896.547739 |
0.81102081 |
7.00E-05 |
2664.075377 |
530167 |
8.836116667 |
0.977634195 |
| 0.517585686 |
0.482414295 |
5955.120603 |
0.820034566 |
6.00E-05 |
2736.81407 |
544626 |
9.0771 |
0.978628231 |
| 0.608033014 |
0.391967066 |
6224.266332 |
0.816065916 |
5.00E-05 |
2806.190955 |
558447 |
9.30745 |
0.980616302 |
| 0.547734512 |
0.452265473 |
6384.939698 |
0.812544332 |
4.00E-05 |
2272.070352 |
452142 |
7.5357 |
0.977137177 |
| 0.482413133 |
0.517586822 |
6846.653266 |
0.841641108 |
3.00E-05 |
3816.567839 |
759513 |
12.65855 |
0.977137177 |
| 0.467337138 |
0.53266287 |
7559.673367 |
0.838746416 |
2.00E-05 |
4074.080402 |
810742 |
13.51236667 |
0.98111332 |
| 0.482412189 |
0.51758781 |
8652.512563 |
0.836461133 |
1.00E-05 |
4456.758794 |
886910 |
14.78183333 |
0.98359841 |
| 0.49246216 |
0.50753784 |
8930.713568 |
0.829363018 |
9.00E-06 |
3990.477387 |
794120 |
13.23533333 |
0.981610338 |
| 0.457286964 |
0.542713038 |
8958.738693 |
0.831638311 |
8.00E-06 |
4401.145729 |
875844 |
14.5974 |
0.984095427 |
| 0.402010924 |
0.597989072 |
9323.19598 |
0.84380401 |
7.00E-06 |
4612.914573 |
917971 |
15.29951667 |
0.984095427 |
| 0.487437406 |
0.512562594 |
9608.979899 |
0.823451252 |
6.00E-06 |
4609.708543 |
917332 |
15.28886667 |
0.980616302 |
| 0.391960666 |
0.60803934 |
10396.34171 |
0.852640439 |
5.00E-06 |
4281.311558 |
851981 |
14.19968333 |
0.98111332 |
| 0.472361979 |
0.527638022 |
11352.55276 |
0.826705596 |
4.00E-06 |
5222.723618 |
1039322 |
17.32203333 |
0.984095427 |
| 0.452261514 |
0.547738488 |
12671.9397 |
0.847979959 |
3.00E-06 |
5722.20603 |
1138719 |
18.97865 |
0.979622266 |
| 0.422110744 |
0.577889256 |
15187.56784 |
0.861167168 |
2.00E-06 |
6329.286432 |
1259543 |
20.99238333 |
0.98111332 |
| 0.381909687 |
0.618090313 |
23370.95477 |
0.890114089 |
1.00E-06 |
9801.537688 |
1950523 |
32.50871667 |
0.984095427 |
| 49*200*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.490818752 |
0.507088157 |
5.874371859 |
0.494575262 |
0.5 |
949.6934673 |
188999 |
3.149983333 |
0.798210736 |
| 0.509046809 |
0.490642269 |
972.9296482 |
0.628590268 |
0.4 |
1381.819095 |
274985 |
4.583083333 |
0.953777336 |
| 0.517038938 |
0.483025644 |
1385.969849 |
0.615358103 |
0.3 |
1564.311558 |
311306 |
5.188433333 |
0.966202783 |
| 0.493811622 |
0.506428399 |
1509.105528 |
0.650374137 |
0.2 |
1618.201005 |
322028 |
5.367133333 |
0.965208748 |
| 0.56022585 |
0.439901883 |
1814.653266 |
0.662469904 |
0.1 |
1750.934673 |
348439 |
5.807316667 |
0.970178926 |
| 0.700795401 |
0.299205507 |
2409.899497 |
0.684338691 |
0.01 |
2034.221106 |
404818 |
6.746966667 |
0.974652087 |
| 0.532577762 |
0.467421389 |
3242.41206 |
0.773122571 |
0.001 |
2401.030151 |
477814 |
7.963566667 |
0.972166998 |
| 0.432167436 |
0.567832557 |
4641.507538 |
0.802121942 |
1.00E-04 |
3004.919598 |
597982 |
9.966366667 |
0.980119284 |
| 0.467334815 |
0.532665203 |
4643.81407 |
0.806148036 |
9.00E-05 |
2996.286432 |
596271 |
9.93785 |
0.977137177 |
| 0.457287144 |
0.542712893 |
4800.718593 |
0.808585672 |
8.00E-05 |
3064.281407 |
609798 |
10.1633 |
0.98359841 |
| 0.492459584 |
0.50754045 |
4944.120603 |
0.794324505 |
7.00E-05 |
3126.844221 |
622246 |
10.37076667 |
0.983101392 |
| 0.467336595 |
0.532663335 |
5034.21608 |
0.807009701 |
6.00E-05 |
3181.005025 |
633028 |
10.55046667 |
0.977634195 |
| 0.487435918 |
0.512564066 |
5301.120603 |
0.800583434 |
5.00E-05 |
3306.537688 |
658008 |
10.9668 |
0.979622266 |
| 0.502510764 |
0.497489206 |
5264.40201 |
0.808977792 |
4.00E-05 |
3294.653266 |
655641 |
10.92735 |
0.977634195 |
| 0.542712177 |
0.457287846 |
5613.075377 |
0.789733958 |
3.00E-05 |
3456.442211 |
687837 |
11.46395 |
0.985089463 |
| 0.567837788 |
0.432162214 |
6100.708543 |
0.784109414 |
2.00E-05 |
3465.296482 |
689611 |
11.49351667 |
0.977634195 |
| 0.497487038 |
0.502512963 |
6956.778894 |
0.800823201 |
1.00E-05 |
3733.180905 |
742919 |
12.38198333 |
0.979125249 |
| 0.562813312 |
0.437186693 |
7182.894472 |
0.803190905 |
9.00E-06 |
3817.226131 |
759628 |
12.66046667 |
0.980616302 |
| 0.497487367 |
0.502512639 |
7194.165829 |
0.818181364 |
8.00E-06 |
3455.874372 |
687719 |
11.46198333 |
0.983101392 |
| 0.532662919 |
0.467337093 |
7430.01005 |
0.795076276 |
7.00E-06 |
3924.321608 |
780955 |
13.01591667 |
0.982107356 |
| 0.547738105 |
0.452261885 |
7687.753769 |
0.820109494 |
6.00E-06 |
4159.291457 |
827714 |
13.79523333 |
0.984095427 |
| 0.512562677 |
0.48743732 |
8213.728643 |
0.807841394 |
5.00E-06 |
4495.723618 |
894650 |
14.91083333 |
0.977634195 |
| 0.402010534 |
0.597989469 |
8421.467337 |
0.826800504 |
4.00E-06 |
3858.728643 |
767890 |
12.79816667 |
0.980119284 |
| 0.492462278 |
0.507537721 |
8811.065327 |
0.808947821 |
3.00E-06 |
4823.788945 |
959936 |
15.99893333 |
0.982604374 |
| 0.462311669 |
0.537688333 |
10138.0402 |
0.822145019 |
2.00E-06 |
5388.236181 |
1072263 |
17.87105 |
0.982107356 |
| 0.442211116 |
0.557788883 |
15122.70352 |
0.82579398 |
1.00E-06 |
6041.266332 |
1202212 |
20.03686667 |
0.979622266 |
| 49*500*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.484243393 |
0.502410251 |
366.4924623 |
0.487584543 |
0.5 |
1279.909548 |
254720 |
4.245333333 |
0.522365805 |
| 0.495580683 |
0.498044608 |
327.4070352 |
0.487267351 |
0.4 |
1252.311558 |
249215 |
4.153583333 |
0.512922465 |
| 0.487374202 |
0.507697813 |
351.1457286 |
0.487172443 |
0.3 |
1271.552764 |
253040 |
4.217333333 |
0.505964215 |
| 0.497630333 |
0.504499464 |
445.1105528 |
0.487077535 |
0.2 |
1329 |
264472 |
4.407866667 |
0.487077535 |
| 0.607517669 |
0.390464489 |
551.9648241 |
0.492489785 |
0.1 |
1395.708543 |
277746 |
4.6291 |
0.742047714 |
| 0.611261889 |
0.388751079 |
1947.155779 |
0.613986933 |
0.01 |
2270.879397 |
451908 |
7.5318 |
0.965208748 |
| 0.733366518 |
0.266634511 |
2687.366834 |
0.627933405 |
0.001 |
2730.798995 |
543430 |
9.057166667 |
0.969681909 |
| 0.542703087 |
0.457296768 |
3755.718593 |
0.74015455 |
1.00E-04 |
2257.301508 |
449219 |
7.486983333 |
0.972166998 |
| 0.457288982 |
0.542710905 |
3834.145729 |
0.771506639 |
9.00E-05 |
3916.949749 |
779475 |
12.99125 |
0.975646123 |
| 0.603003264 |
0.396996665 |
4004.120603 |
0.720099004 |
8.00E-05 |
4228.713568 |
841530 |
14.0255 |
0.969681909 |
| 0.497486907 |
0.502513117 |
3983.703518 |
0.748508946 |
7.00E-05 |
4218.834171 |
839548 |
13.99246667 |
0.97415507 |
| 0.552756415 |
0.447243651 |
4338.090452 |
0.743708603 |
6.00E-05 |
4466.100503 |
888755 |
14.81258333 |
0.976640159 |
| 0.482410699 |
0.517589313 |
4155.115578 |
0.770442671 |
5.00E-05 |
3232.58794 |
643286 |
10.72143333 |
0.972664016 |
| 0.532658616 |
0.467341398 |
4743.256281 |
0.739782411 |
4.00E-05 |
4756.20603 |
946500 |
15.775 |
0.971172962 |
| 0.462312642 |
0.537687347 |
4725.738693 |
0.776549247 |
3.00E-05 |
4661.301508 |
927599 |
15.45998333 |
0.977137177 |
| 0.41206262 |
0.58793738 |
5045.266332 |
0.799784209 |
2.00E-05 |
4864.140704 |
967964 |
16.13273333 |
0.978628231 |
| 0.477386962 |
0.522613035 |
5789.261307 |
0.78777336 |
1.00E-05 |
4230.582915 |
841905 |
14.03175 |
0.982107356 |
| 0.502512238 |
0.497487764 |
5733.809045 |
0.778157687 |
9.00E-06 |
5210.969849 |
1036999 |
17.28331667 |
0.977634195 |
| 0.482412254 |
0.517587754 |
5806.984925 |
0.788430223 |
8.00E-06 |
5248.959799 |
1044559 |
17.40931667 |
0.981610338 |
| 0.542713234 |
0.457286764 |
6073.266332 |
0.769011559 |
7.00E-06 |
4482.698492 |
892057 |
14.86761667 |
0.98111332 |
| 0.552763372 |
0.447236625 |
6300.633166 |
0.761471373 |
6.00E-06 |
5563.964824 |
1107229 |
18.45381667 |
0.979622266 |
| 0.572863836 |
0.427136156 |
6550.331658 |
0.757295423 |
5.00E-06 |
5878.944724 |
1169918 |
19.49863333 |
0.980119284 |
| 0.502512496 |
0.4974875 |
6433.165829 |
0.786929179 |
4.00E-06 |
4777.959799 |
950814 |
15.8469 |
0.979622266 |
| 0.507537594 |
0.492462406 |
6982.005025 |
0.790405806 |
3.00E-06 |
5974.507538 |
1188943 |
19.81571667 |
0.982604374 |
| 0.582914394 |
0.417085605 |
7838.643216 |
0.765687283 |
2.00E-06 |
6632.708543 |
1319910 |
21.9985 |
0.980119284 |
| 0.437185993 |
0.562814006 |
9934.658291 |
0.802459115 |
1.00E-06 |
7109.241206 |
1414739 |
23.57898333 |
0.979622266 |
| 49*1000*2 |
||||||||
| 02 |
||||||||
| f2[0] |
f2[1] |
迭代次数n |
平均准确率p-ave |
δ |
耗时ms/次 |
耗时ms/199次 |
耗时 min/199 |
最大准确率p-max |
| 0.474436803 |
0.540625584 |
427.3366834 |
0.517270748 |
0.5 |
1986.487437 |
395327 |
6.588783333 |
0.924950298 |
| 0.487783436 |
0.512635249 |
416.7386935 |
0.498626333 |
0.4 |
2002.798995 |
398558 |
6.642633333 |
0.863817097 |
| 0.482349775 |
0.529512002 |
495.2914573 |
0.49425807 |
0.3 |
2081.180905 |
414156 |
6.9026 |
0.802186879 |
| 0.47559663 |
0.52254396 |
431.7738693 |
0.488423729 |
0.2 |
2006.180905 |
399230 |
6.653833333 |
0.705765408 |
| 0.583834467 |
0.411853739 |
538 |
0.488656004 |
0.1 |
1155.567839 |
229958 |
3.832633333 |
0.792246521 |
| 0.476756262 |
0.523245651 |
958.5577889 |
0.536127457 |
0.01 |
2497.261307 |
496970 |
8.282833333 |
0.946819085 |
| 0.688209894 |
0.311796064 |
2178.155779 |
0.580796627 |
0.001 |
3698.407035 |
735984 |
12.2664 |
0.970675944 |
| 0.577877907 |
0.422121811 |
3671.733668 |
0.689735956 |
1.00E-04 |
4938.753769 |
982812 |
16.3802 |
0.979622266 |
| 0.572856892 |
0.427143081 |
3766.914573 |
0.695053298 |
9.00E-05 |
5032.432161 |
1001454 |
16.6909 |
0.976143141 |
| 0.567830627 |
0.432169342 |
3537.552764 |
0.703972147 |
8.00E-05 |
4209.311558 |
837654 |
13.9609 |
0.97415507 |
| 0.613054741 |
0.386945311 |
3755.638191 |
0.682770213 |
7.00E-05 |
5028.653266 |
1000718 |
16.67863333 |
0.976640159 |
| 0.582907771 |
0.417092245 |
3795.145729 |
0.692630648 |
6.00E-05 |
5085.879397 |
1012107 |
16.86845 |
0.977634195 |
| 0.507535752 |
0.492464205 |
3860.778894 |
0.723480724 |
5.00E-05 |
4454.110553 |
886384 |
14.77306667 |
0.979125249 |
| 0.497484959 |
0.502515036 |
3863.552764 |
0.735733838 |
4.00E-05 |
5143.864322 |
1023644 |
17.06073333 |
0.970675944 |
| 0.47738749 |
0.522612451 |
4506.376884 |
0.744467866 |
3.00E-05 |
5648.658291 |
1124088 |
18.7348 |
0.972166998 |
| 0.497487087 |
0.502512879 |
4465.934673 |
0.741033697 |
2.00E-05 |
5538.075377 |
1102081 |
18.36801667 |
0.97415507 |
| 0.432161237 |
0.567838772 |
4991.507538 |
0.777658172 |
1.00E-05 |
5719.507538 |
1138190 |
18.96983333 |
0.973161034 |
| 0.517587173 |
0.482412812 |
5153.572864 |
0.749065906 |
9.00E-06 |
6178.884422 |
1229602 |
20.49336667 |
0.978131213 |
| 0.477387016 |
0.522612981 |
5193.623116 |
0.756336354 |
8.00E-06 |
6219.175879 |
1237620 |
20.627 |
0.977137177 |
| 0.497487343 |
0.502512649 |
5183.844221 |
0.764026394 |
7.00E-06 |
6214.276382 |
1236645 |
20.61075 |
0.980119284 |
| 0.502512325 |
0.49748767 |
5706.01005 |
0.761114219 |
6.00E-06 |
6682.919598 |
1329904 |
22.16506667 |
0.978131213 |
| 0.492462237 |
0.507537759 |
6091.135678 |
0.761211625 |
5.00E-06 |
7197.809045 |
1432364 |
23.87273333 |
0.98111332 |
| 0.507537656 |
0.492462346 |
5787.120603 |
0.756253934 |
4.00E-06 |
5448.844221 |
1084326 |
18.0721 |
0.978131213 |
| 0.56783893 |
0.432161068 |
6397.271357 |
0.750984045 |
3.00E-06 |
6805.41206 |
1354280 |
22.57133333 |
0.979125249 |
| 0.512562779 |
0.487437214 |
6485.407035 |
0.776431861 |
2.00E-06 |
5836.271357 |
1161419 |
19.35698333 |
0.98111332 |
| 0.467336727 |
0.532663274 |
8098.125628 |
0.787905731 |
1.00E-06 |
8209.713568 |
1633733 |
27.22888333 |
0.983101392 |
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0.459394392 0.502369343 2 0.512922465 0.5 900
0.481869433 0.507651392 2 0.512922465 0.5 856
0.500366948 0.498330097 61 0.487077535 0.5 863
0.501097859 0.499857947 61 0.487077535 0.5 843
0.500216699 0.493081051 1 0.487077535 0.5 756
0.501437235 0.499928729 49 0.487077535 0.5 789
0.499905878 0.500424287 68 0.513916501 0.5 839
0.498576787 0.500396847 60 0.522365805 0.5 782
0.500008438 0.497697541 33 0.487077535 0.5 745
0.498591795 0.58393129 2 0.512922465 0.5 801
0.534247205 0.465598787 1 0.487077535 0.5 764
0.490436625 0.500053904 18 0.512922465 0.5 777
0.533263882 0.461649561 1 0.487077535 0.5 749
0.540741314 0.489632457 1 0.487077535 0.5 772
0.534638384 0.448776442 1 0.487077535 0.5 814
0.499783505 0.501088264 54 0.555666004 0.5 829
0.500188281 0.499278863 57 0.487077535 0.5 832
0.499662445 0.501416595 32 0.570576541 0.5 794
0.499752015 0.504300383 26 0.512922465 0.5 782
0.492288953 0.502453383 2 0.512922465 0.5 832
0.499950194 0.500955496 50 0.511431412 0.5 791
0.516331957 0.480104715 1 0.487077535 0.5 772
0.464315103 0.507699267 2 0.512922465 0.5 778
0.497502203 0.501384608 60 0.514413519 0.5 787
0.467726867 0.576514512 2 0.512922465 0.5 737
0.517268014 0.486370855 1 0.487077535 0.5 775
0.500141213 0.496969126 41 0.487077535 0.5 795
0.500893784 0.499691926 61 0.487077535 0.5 787
0.500257492 0.499842473 57 0.487077535 0.5 810
0.500270547 0.498432189 63 0.487077535 0.5 789
0.501463773 0.499669211 49 0.487077535 0.5 763
0.436102828 0.550026649 2 0.512922465 0.5 805
0.49976234 0.500823763 48 0.519383698 0.5 779
0.507623823 0.476173143 1 0.487077535 0.5 793
0.474108416 0.516002842 2 0.512922465 0.5 752
0.499343727 0.50207071 50 0.512922465 0.5 795
0.516935926 0.439992279 1 0.487077535 0.5 755
0.481751516 0.508460219 2 0.512922465 0.5 776
0.500296556 0.498186218 55 0.487077535 0.5 815
0.531954707 0.461092639 1 0.487077535 0.5 785
0.499635111 0.50772015 36 0.512922465 0.5 772
0.499801642 0.506250975 36 0.512922465 0.5 778
0.499976771 0.501457138 64 0.72415507 0.5 759
0.500136815 0.498973301 39 0.487077535 0.5 840
0.497803917 0.500337146 32 0.541252485 0.5 845
0.499674053 0.500353866 58 0.771868787 0.5 783
0.510967407 0.485072283 1 0.487077535 0.5 741
0.581558025 0.497460684 1 0.487077535 0.5 736
0.49997251 0.503105378 48 0.512922465 0.5 777
0.500170591 0.498292268 59 0.487077535 0.5 749
0.48274115 0.50904889 2 0.512922465 0.5 738
0.500076171 0.499382965 61 0.487077535 0.5 813
0.49745774 0.500838032 58 0.512922465 0.5 801
0.480751088 0.535761365 2 0.512922465 0.5 784
0.412355673 0.519095333 2 0.512922465 0.5 759
0.470647741 0.509157105 2 0.512922465 0.5 820
0.498893775 0.510982933 2 0.512922465 0.5 768
0.467513358 0.512177309 2 0.512922465 0.5 778
0.500344901 0.499093139 47 0.487077535 0.5 748
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0.500608613 0.49990207 67 0.487077535 0.5 765
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0.500069782 0.492024222 19 0.487077535 0.5 790
0.526075323 0.486100805 1 0.487077535 0.5 771
0.542049926 0.476988926 1 0.487077535 0.5 797
0.500162648 0.49868371 53 0.487077535 0.5 771
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0.471201868 0.509656248 2 0.512922465 0.5 787
0.482014928 0.517174494 2 0.512922465 0.5 785
0.500173167 0.498024085 27 0.487077535 0.5 802
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0.496638815 0.500064337 50 0.548210736 0.5 751
0.508839379 0.490457372 1 0.487077535 0.5 763
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0.500082709 0.495158443 41 0.487077535 0.5 751
0.580378383 0.474949299 1 0.487077535 0.5 727
0.445591985 0.518587763 2 0.512922465 0.5 749
0.524378564 0.499460043 5 0.487077535 0.5 753
0.533008365 0.469919659 1 0.487077535 0.5 786
0.497770784 0.500365275 58 0.514910537 0.5 819
0.521320972 0.486090356 1 0.487077535 0.5 790
0.499671449 0.500810069 58 0.676441352 0.5 805
0.515177509 0.490814485 1 0.487077535 0.5 741
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0.499837696 0.501191651 38 0.513419483 0.5 783
0.505816767 0.484304361 1 0.487077535 0.5 778
0.501240013 0.498663287 65 0.487077535 0.5 780
0.49917673 0.53430702 4 0.512922465 0.5 763
0.498771749 0.500203147 64 0.512922465 0.5 796
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0.526387037 0.490806175 1 0.487077535 0.5 769
0.485783678 0.509799182 2 0.512922465 0.5 756
0.518512481 0.459782589 1 0.487077535 0.5 736
0.499996125 0.501380913 58 0.60387674 0.5 816
0.485591627 0.504898672 2 0.512922465 0.5 755
0.505541453 0.452406802 1 0.487077535 0.5 803
0.468054777 0.545237557 2 0.512922465 0.5 757
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0.497898674 0.500403232 54 0.509940358 0.5 768
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0.469773421 0.541625416 2 0.512922465 0.5 783
0.500078656 0.497902889 57 0.487077535 0.5 802
0.518264099 0.49043547 1 0.487077535 0.5 787
0.500000287 0.498239469 47 0.487077535 0.5 769
0.497804903 0.500212718 30 0.512922465 0.5 797
0.540916261 0.487215636 1 0.487077535 0.5 759
0.51509185 0.489868013 1 0.487077535 0.5 783
0.501205181 0.466229567 1 0.487077535 0.5 755
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0.498936088 0.500157694 62 0.516898608 0.5 819
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0.500756502 0.487037264 1 0.487077535 0.5 748
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0.534024738 0.48696477 1 0.487077535 0.5 720
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0.499164858 0.500125846 54 0.606858847 0.5 752
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0.50046493 0.499606788 49 0.487077535 0.5 767
0.452525858 0.542059516 2 0.512922465 0.5 736
0.498808321 0.500237754 82 0.590954274 0.5 783
0.485779953 0.54196954 2 0.512922465 0.5 752
0.469979278 0.510072794 2 0.512922465 0.5 737
0.500132195 0.496434508 35 0.487077535 0.5 768
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0.496802518 0.500414825 40 0.512922465 0.5 735
0.479382289 0.520086266 2 0.512922465 0.5 737
0.539033186 0.462582477 1 0.487077535 0.5 720
0.49187405 0.524248569 2 0.512922465 0.5 762
0.471001153 0.513019269 2 0.512922465 0.5 737
0.500718134 0.499794638 59 0.487077535 0.5 753
0.504015652 0.499986651 43 0.487077535 0.5 809
0.499316461 0.500289618 60 0.809642147 0.5 814
0.481214999 0.528192607 2 0.512922465 0.5 720
0.500395621 0.499237538 67 0.487077535 0.5 779
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0.50469036 0.481241583 1 0.487077535 0.5 732
0.499916063 0.500472668 66 0.516898608 0.5 780
0.521051392 0.484166814 1 0.487077535 0.5 732
0.500488466 0.499248859 65 0.487077535 0.5 778
0.511396296 0.495016732 1 0.487077535 0.5 748
0.498927212 0.500652559 56 0.512922465 0.5 720
0.464558564 0.530300567 2 0.512922465 0.5 749
0.497480898 0.500518794 64 0.508946322 0.5 747
0.492527326 0.530515843 2 0.512922465 0.5 719
0.497823088 0.500010401 42 0.510437376 0.5 745
0.499890273 0.500068981 36 0.519880716 0.5 747
0.498362928 0.537346869 2 0.512922465 0.5 805
0.501457467 0.49994007 57 0.487077535 0.5 778
0.522203549 0.496870108 1 0.487077535 0.5 787
0.521249128 0.433445545 1 0.487077535 0.5 779
0.500094751 0.494760852 33 0.487077535 0.5 756
0.499376984 0.502353888 40 0.512922465 0.5 754
0.498398548 0.500012101 54 0.513419483 0.5 765
0.497093395 0.500140728 48 0.512922465 0.5 759
0.497124486 0.500879285 40 0.512922465 0.5 771
0.500030983 0.497063527 3 0.487077535 0.5 718
0.53490261 0.455110197 1 0.487077535 0.5 787
0.528390708 0.490688903 1 0.487077535 0.5 758
0.499966382 0.501099573 52 0.624751491 0.5 846
0.499011699 0.500016141 58 0.716699801 0.5 796
0.50016688 0.497116335 41 0.487077535 0.5 780
0.51339695 0.499903908 1 0.487077535 0.5 744
154421
0.382691254 0.622098551 1252 0.961232604 0.4 1181
0.390099734 0.609750391 1802 0.948807157 0.4 1400
0.399101817 0.606151319 1508 0.949304175 0.4 1257
0.396443079 0.610031876 2502 0.959741551 0.4 1654
0.618159743 0.389247434 1685 0.581510934 0.4 1285
0.387905342 0.610484759 2030 0.922962227 0.4 1390
0.6096395 0.394355437 1285 0.85387674 0.4 1180
0.60196283 0.399682552 5061 0.530815109 0.4 2475
0.600584061 0.399784661 1431 0.861332008 0.4 1239
0.601483512 0.395170889 2037 0.669483101 0.4 1432
0.396998422 0.604575765 2832 0.916003976 0.4 1694
0.602633419 0.396634152 2213 0.718190855 0.4 1500
0.60015481 0.394123318 1547 0.766898608 0.4 1315
0.605310823 0.39513366 1373 0.716202783 0.4 1183
0.606833039 0.391228204 2305 0.551689861 0.4 1557
0.602379821 0.397084553 1865 0.679920477 0.4 1405
0.601664048 0.396659059 2479 0.667992048 0.4 1576
0.398900947 0.602610268 1780 0.960735586 0.4 1388
0.619920931 0.382843069 1981 0.692345924 0.4 1428
0.614778327 0.388790908 1431 0.799701789 0.4 1229
0.609489896 0.388863504 1685 0.711232604 0.4 1354
0.382068775 0.617374658 1990 0.935387674 0.4 1459
0.38976525 0.606030062 2020 0.929423459 0.4 1432
0.39799077 0.600817041 1946 0.94333996 0.4 1385
0.393891067 0.60733701 1104 0.962723658 0.4 1149
0.389626514 0.608503879 1926 0.94582505 0.4 1481
0.625911304 0.37840517 1591 0.86332008 0.4 1274
0.393828517 0.600121827 2074 0.91500994 0.4 1399
0.612006947 0.391840988 2021 0.821570577 0.4 1450
0.388430704 0.6054298 1610 0.919980119 0.4 1324
0.607085223 0.397050957 1625 0.763419483 0.4 1354
0.627911818 0.381384961 1285 0.887176938 0.4 1196
0.628974131 0.378152846 1285 0.838469185 0.4 1170
0.396064182 0.604483225 2570 0.93638171 0.4 1625
0.61714814 0.380148482 1701 0.499005964 0.4 1366
0.609452701 0.387340755 2119 0.682902584 0.4 1513
0.601503604 0.391456549 2449 0.697813121 0.4 1553
0.398785344 0.601240688 1462 0.964214712 0.4 1238
0.609575528 0.38960618 1701 0.531809145 0.4 1316
0.399259479 0.600593663 1080 0.966202783 0.4 1168
0.608677443 0.39975901 1865 0.713717694 0.4 1419
0.390605165 0.609342502 2490 0.954771372 0.4 1588
0.395562166 0.607397244 1946 0.93638171 0.4 1389
0.390564434 0.604758375 1926 0.962723658 0.4 1449
0.39630652 0.603124529 1674 0.971172962 0.4 1332
0.376840826 0.620620537 1664 0.949304175 0.4 1326
0.609573543 0.388651745 2401 0.600397614 0.4 1538
0.61204936 0.385510508 1913 0.708250497 0.4 1433
0.606920544 0.399306617 1981 0.656063618 0.4 1408
0.60789833 0.395210923 2065 0.868787276 0.4 1465
0.393587418 0.617291421 1802 0.944831014 0.4 1349
0.383921882 0.616719948 2616 0.916998012 0.4 1653
0.600326681 0.399997758 1431 0.749005964 0.4 1253
0.601150585 0.393887501 1155 0.700795229 0.4 1154
0.601884878 0.396704904 1685 0.615805169 0.4 1306
0.615506544 0.378444004 1517 0.824552684 0.4 1262
0.600902644 0.396688848 2911 0.617793241 0.4 1685
0.601402613 0.393915312 1985 0.723658052 0.4 1449
0.607286568 0.389312299 1721 0.710735586 0.4 1359
0.615163534 0.382221322 1721 0.694333996 0.4 1289
0.611216329 0.393068327 1865 0.760437376 0.4 1417
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0.398321133 0.601301845 3048 0.929920477 0.4 1788
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0.394915791 0.603265898 1674 0.934890656 0.4 1370
0.395433785 0.601776618 1470 0.956262425 0.4 1208
0.601580504 0.394446538 2879 0.499502982 0.4 1782
0.389697284 0.611918045 3674 0.932902584 0.4 1994
0.372835095 0.63046967 1802 0.924950298 0.4 1398
0.392716295 0.603866715 1420 0.957256461 0.4 1213
0.616262277 0.388408565 1913 0.844930417 0.4 1377
0.396662061 0.610003476 1366 0.950298211 0.4 1218
0.607062406 0.390190468 1529 0.634194831 0.4 1292
0.61723315 0.387156567 2263 0.492047714 0.4 1556
0.603405699 0.39663833 2847 0.557654076 0.4 1678
0.613067864 0.384984384 1591 0.575049702 0.4 1275
0.387531009 0.608690027 2806 0.819085487 0.4 1697
0.603798132 0.398564436 1865 0.722664016 0.4 1411
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0.619116257 0.380724555 2195 0.647614314 0.4 1485
0.392280433 0.609649924 1802 0.945328032 0.4 1349
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0.610159989 0.383344304 2635 0.582007952 0.4 1660
0.614618765 0.386980776 1913 0.848906561 0.4 1384
0.607232345 0.391970693 2045 0.69582505 0.4 1484
0.3839474 0.614955481 2224 0.941848907 0.4 1522
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0.638632538 0.361013289 1155 0.820576541 0.4 1137
0.398809836 0.601841577 1940 0.894135189 0.4 1457
0.614449335 0.389327778 2065 0.585984095 0.4 1426
0.61269902 0.385042003 5819 0.616302187 0.4 2782
0.393340999 0.605151762 1552 0.957753479 0.4 1275
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0.373403049 0.621513216 2224 0.955765408 0.4 1546
0.61539037 0.38066258 1237 0.800198807 0.4 1190
0.613831648 0.386528465 1285 0.8444334 0.4 1165
0.603012769 0.388171877 2647 0.612823062 0.4 1643
0.606999675 0.390391953 1905 0.913518887 0.4 1393
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0.39811597 0.600434577 2832 0.946819085 0.4 1691
0.393524302 0.603766724 3048 0.972166998 0.4 1785
0.602665067 0.399233908 1913 0.714214712 0.4 1400
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0.604905589 0.394798664 2389 0.804671968 0.4 1576
0.399232291 0.600063926 1610 0.954274354 0.4 1268
0.613381891 0.38527782 2227 0.726143141 0.4 1486
0.60849469 0.396500364 1591 0.573558648 0.4 1335
0.611130919 0.388379206 1603 0.720178926 0.4 1248
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0.61373703 0.393087728 1775 0.822564612 0.4 1378
0.603357516 0.391559489 1133 0.763916501 0.4 1104
0.612308783 0.390053568 1331 0.815606362 0.4 1178
0.383636104 0.608338854 2168 0.922465209 0.4 1463
0.388228465 0.609598774 2366 0.939860835 0.4 1543
0.607366312 0.394948535 2305 0.573558648 0.4 1556
0.392934387 0.602715985 1946 0.948310139 0.4 1412
0.613407674 0.382101282 2263 0.559145129 0.4 1516
0.390265059 0.607649556 1552 0.941848907 0.4 1279
0.608987672 0.392641015 1985 0.741053678 0.4 1439
0.398127723 0.604612956 2622 0.914512922 0.4 1640
0.61444647 0.386361454 2333 0.627733598 0.4 1562
0.612831193 0.386285458 1353 0.657057654 0.4 1201
0.390054443 0.611409979 1674 0.961729622 0.4 1345
0.614246928 0.39322567 2119 0.729125249 0.4 1519
0.390939932 0.607965083 1652 0.9527833 0.4 1286
0.604973142 0.396736534 2625 0.709741551 0.4 1611
0.390798441 0.61073428 1450 0.916003976 0.4 1309
0.371848982 0.628062397 1926 0.959244533 0.4 1414
0.372229445 0.623090667 1946 0.895129225 0.4 1450
0.604616162 0.396832845 1361 0.836978131 0.4 1220
0.603534941 0.399168993 2195 0.572564612 0.4 1450
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0.608628275 0.389356647 1775 0.850397614 0.4 1353
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0.605812922 0.398599017 1087 0.89860835 0.4 1111
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0.398951416 0.600844136 1286 0.943836978 0.4 1180
0.604930904 0.395755839 2509 0.646620278 0.4 1559
283133
0.294002284 0.708076933 2030 0.969184891 0.3 1463
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0.702231465 0.298626491 1981 0.879224652 0.3 1383
0.705013771 0.297111021 1905 0.913021869 0.3 1410
0.701465695 0.298477342 1981 0.879224652 0.3 1420
0.711945015 0.287537544 3441 0.643141153 0.3 1915
0.284710577 0.700627279 1130 0.951789264 0.3 1160
0.710880383 0.288387983 2711 0.770874751 0.3 1698
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0.701358268 0.297328219 2611 0.895129225 0.3 1667
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0.726956832 0.266096779 2119 0.89612326 0.3 1450
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0.706745087 0.299094632 2521 0.821570577 0.3 1641
0.294329456 0.707594279 2224 0.930417495 0.3 1468
0.280798304 0.721968016 2030 0.948310139 0.3 1398
0.297153002 0.704399431 2558 0.922962227 0.3 1659
0.717968591 0.2807039 2305 0.824552684 0.3 1582
0.731644447 0.268272839 2049 0.922465209 0.3 1445
0.715314056 0.284725168 2119 0.828528827 0.3 1459
0.295478292 0.706159808 2820 0.958747515 0.3 1690
0.275660069 0.724268237 1664 0.97166998 0.3 1320
0.715649751 0.286865046 3441 0.545725646 0.3 1923
0.288853094 0.710127205 2020 0.900099404 0.3 1479
0.253595698 0.748447679 3150 0.877236581 0.3 1828
0.70365189 0.294420562 2635 0.66500994 0.3 1704
0.285621982 0.709378462 3380 0.939363817 0.3 1878
0.284703201 0.713294698 2730 0.903578529 0.3 1661
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0.702932968 0.298582084 1517 0.843439364 0.3 1246
0.299189976 0.700155196 1780 0.947316103 0.3 1340
0.738047764 0.262624744 2879 0.632703777 0.3 1729
0.290404649 0.711412802 1552 0.968190855 0.3 1267
0.716381634 0.281110929 2739 0.803677932 0.3 1700
0.706030994 0.298173014 1707 0.78528827 0.3 1308
0.715323184 0.288941876 2305 0.845427435 0.3 1522
0.71047227 0.290829209 1285 0.928926441 0.3 1166
0.708828821 0.285791095 1899 0.944831014 0.3 1410
0.729209413 0.276002971 1603 0.889662028 0.3 1282
0.258204317 0.744604903 3150 0.94333996 0.3 1834
0.710173146 0.291196124 3005 0.784791252 0.3 1720
0.298358284 0.710884055 1890 0.919980119 0.3 1369
0.264692273 0.731293597 1552 0.959741551 0.3 1281
0.710419595 0.296401635 4207 0.767395626 0.3 2162
0.714111374 0.287376492 2113 0.913518887 0.3 1428
0.299811271 0.703751899 2064 0.937375746 0.3 1448
0.297431312 0.700901926 3880 0.920974155 0.3 2064
0.705294594 0.298321503 1721 0.821570577 0.3 1306
0.708652209 0.298475851 2411 0.780318091 0.3 1602
0.707598215 0.284204645 3019 0.758449304 0.3 1782
0.295153291 0.701704066 2818 0.918986083 0.3 1691
0.280341023 0.717286282 2814 0.902087475 0.3 1676
0.703375268 0.296822656 3219 0.533300199 0.3 1838
0.288646198 0.716970548 1978 0.906560636 0.3 1371
0.287776549 0.708951271 3978 0.823558648 0.3 2129
0.70068005 0.296106533 2883 0.808151093 0.3 1771
0.706290666 0.29226285 2119 0.727634195 0.3 1445
0.714847284 0.285266504 2413 0.924950298 0.3 1556
0.290074191 0.706658529 2950 0.934393638 0.3 1841
0.26677547 0.733210872 1802 0.936878728 0.3 1344
0.289207414 0.714646973 3150 0.942345924 0.3 1889
0.288292365 0.707686178 1206 0.935884692 0.3 1138
0.709028465 0.291176227 2401 0.748011928 0.3 1561
0.291192567 0.712877728 1664 0.945328032 0.3 1331
0.704842587 0.296519716 1285 0.905069583 0.3 1216
0.722752673 0.277872087 2109 0.819582505 0.3 1462
0.289758873 0.706937312 2008 0.919980119 0.3 1424
0.287970271 0.708963787 2958 0.931908549 0.3 1789
0.742324747 0.251090057 1353 0.783797217 0.3 1192
0.289240033 0.705711754 1890 0.969681909 0.3 1384
0.278058507 0.716958481 2202 0.930914513 0.3 1516
0.275416082 0.728105997 2224 0.931908549 0.3 1503
0.751463957 0.250607284 2109 0.80417495 0.3 1476
0.701741034 0.297774773 4833 0.542743539 0.3 2383
0.71688273 0.278808164 2577 0.769880716 0.3 1612
0.717616564 0.281599922 4443 0.708747515 0.3 2294
0.712017866 0.291531001 1691 0.738071571 0.3 1311
0.711443323 0.28547121 1981 0.819085487 0.3 1411
0.705863044 0.298247445 2051 0.954274354 0.3 1463
0.28957253 0.703933098 1664 0.969184891 0.3 1331
0.712714673 0.287203621 2623 0.562624254 0.3 1647
0.295251652 0.708099548 1258 0.960238569 0.3 1146
0.706277121 0.293894596 1721 0.86083499 0.3 1328
0.289854181 0.700951003 1184 0.9527833 0.3 1194
0.295533195 0.706996568 1666 0.944831014 0.3 1328
0.703341982 0.297503932 1653 0.837972167 0.3 1298
0.285869993 0.716659989 1552 0.951789264 0.3 1230
0.29748162 0.700398141 1552 0.959741551 0.3 1266
0.289434223 0.709229792 3112 0.928926441 0.3 1805
0.275018174 0.718612307 2832 0.904075547 0.3 1708
0.277646018 0.722540145 2050 0.941848907 0.3 1468
0.740175021 0.261017897 2263 0.552683897 0.3 1511
0.270134714 0.728530171 1018 0.967196819 0.3 1111
0.296436939 0.700876934 1206 0.961729622 0.3 1186
0.297561826 0.703666969 2374 0.926441352 0.3 1563
0.728232954 0.276640511 1685 0.850894632 0.3 1309
0.271845915 0.724710822 1890 0.94333996 0.3 1333
0.296377702 0.706583037 2008 0.889662028 0.3 1407
0.706960238 0.2867171 1865 0.802186879 0.3 1391
0.26181563 0.744533873 1552 0.931411531 0.3 1294
0.297577465 0.704815947 1890 0.927435388 0.3 1398
0.706166679 0.291917405 1603 0.83499006 0.3 1281
0.295822198 0.705051906 2406 0.957753479 0.3 1553
0.294745619 0.700058171 1990 0.949801193 0.3 1444
0.293228869 0.708129185 1946 0.947813121 0.3 1433
0.705008 0.298112389 2119 0.800198807 0.3 1419
0.7160186 0.285920567 2635 0.783797217 0.3 1626
0.710229229 0.294547772 2879 0.75695825 0.3 1728
0.728220281 0.277158983 2625 0.859840954 0.3 1632
0.291277376 0.701294147 1666 0.950298211 0.3 1256
0.282801367 0.717694548 3380 0.929920477 0.3 1907
0.740850098 0.258776591 1799 0.867793241 0.3 1415
0.297410596 0.704690651 2030 0.958747515 0.3 1478
0.72231315 0.274393656 2879 0.847415507 0.3 1642
0.721137832 0.276550424 2401 0.81610338 0.3 1525
0.28953569 0.71136736 2596 0.923956262 0.3 1640
0.753914189 0.247678909 2191 0.741053678 0.3 1503
0.282948384 0.704345538 1664 0.933399602 0.3 1290
0.269319424 0.722797583 1890 0.958747515 0.3 1424
0.280361791 0.72010398 1802 0.947813121 0.3 1376
0.290548847 0.712080706 1990 0.944333996 0.3 1360
0.71079205 0.285875589 2477 0.779324056 0.3 1611
0.28332834 0.717439002 2730 0.909045726 0.3 1639
0.717818446 0.26707255 2397 0.887673956 0.3 1544
0.70900849 0.294610536 2911 0.827534791 0.3 1737
0.29937791 0.701708046 1990 0.927932406 0.3 1402
0.287319007 0.716396475 2312 0.916003976 0.3 1504
0.739358734 0.259265041 3019 0.807157058 0.3 1822
0.709286446 0.298989573 2863 0.77584493 0.3 1674
0.266539676 0.734578265 1802 0.966699801 0.3 1332
0.289031784 0.713473101 1780 0.961232604 0.3 1364
0.290993058 0.709291511 2976 0.927932406 0.3 1726
0.278877136 0.716794308 1802 0.953280318 0.3 1331
0.282570614 0.722107608 2558 0.959244533 0.3 1635
0.707466525 0.293801678 3123 0.826043738 0.3 1807
0.284477181 0.720938696 1292 0.956262425 0.3 1191
0.278727693 0.716983218 3862 0.868290258 0.3 2047
0.286155142 0.721041093 2502 0.944831014 0.3 1608
0.70867454 0.278626482 1353 0.785785288 0.3 1227
0.722604291 0.274152043 1353 0.816600398 0.3 1163
0.714460156 0.289515179 1603 0.867793241 0.3 1312
0.296861066 0.702186507 5122 0.860337972 0.3 2492
0.289744406 0.707328067 2564 0.94333996 0.3 1630
0.29782198 0.710960781 3024 0.907554672 0.3 1802
0.719635142 0.269470707 1331 0.920974155 0.3 1167
0.726134826 0.272855437 3417 0.7972167 0.3 1914
0.281437865 0.718594686 2730 0.899105368 0.3 1699
0.253867884 0.748555478 1990 0.961232604 0.3 1391
0.294051903 0.701978218 1890 0.940854871 0.3 1368
0.267440766 0.726527869 3302 0.914512922 0.3 1857
0.28434881 0.712160021 1462 0.967693837 0.3 1223
0.297577516 0.701917804 2938 0.940357853 0.3 1703
0.25909241 0.732657274 2800 0.908548708 0.3 1741
0.727299411 0.278021282 2065 0.761431412 0.3 1486
0.713745712 0.286273518 3417 0.77833002 0.3 1879
0.289713665 0.713754294 1516 0.91749503 0.3 1256
0.708282281 0.295699168 2449 0.914015905 0.3 1570
0.279836754 0.719194119 2984 0.887673956 0.3 1769
0.258999527 0.740063561 1802 0.941848907 0.3 1328
0.707887976 0.295329508 1591 0.897117296 0.3 1293
0.728338917 0.275831222 2635 0.727137177 0.3 1672
0.274497936 0.724999513 2050 0.956262425 0.3 1447
0.718021869 0.272497759 2191 0.809642147 0.3 1457
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0.717530429 0.281546597 4443 0.653081511 0.3 2298
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306062
0.816986953 0.177263503 2781 0.918986083 0.2 1700
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0.823812578 0.175567879 3337 0.833996024 0.2 1832
0.81191017 0.191359312 7989 0.643638171 0.2 3533
0.153942015 0.838743428 1252 0.961729622 0.2 1165
0.808649029 0.18271633 2305 0.860337972 0.2 1504
0.838862991 0.156975952 2191 0.763419483 0.2 1496
0.800243153 0.197033357 1905 0.950795229 0.2 1364
0.817629273 0.178790378 2479 0.938866799 0.2 1601
0.802600999 0.199648459 4291 0.75695825 0.2 2162
0.165806735 0.831319498 2224 0.88916501 0.2 1570
0.824828605 0.182107707 1917 0.935387674 0.2 1369
0.810384438 0.190221128 2411 0.823558648 0.2 1536
0.196004335 0.804472731 2224 0.905069583 0.2 1516
0.17129189 0.832734828 2050 0.938866799 0.2 1468
0.184210454 0.819936578 1946 0.939363817 0.2 1415
0.196704349 0.807434085 3576 0.93638171 0.2 1931
0.818037313 0.181546642 2145 0.92693837 0.2 1447
0.193688445 0.80100945 3290 0.852385686 0.2 1896
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0.800915899 0.199765435 1633 0.922962227 0.2 1375
0.198055606 0.809635447 1990 0.944333996 0.2 1468
0.198397992 0.805254595 1780 0.963220676 0.2 1325
0.19967998 0.802920082 1890 0.963220676 0.2 1391
0.803094896 0.195487194 2485 0.852882704 0.2 1560
0.805724507 0.19671289 1865 0.918489066 0.2 1350
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0.173122869 0.825149399 3150 0.903081511 0.2 1831
0.814912114 0.177874359 1721 0.917992048 0.2 1361
0.85010587 0.144204509 2195 0.787276342 0.2 1479
0.807342398 0.19533372 2625 0.852385686 0.2 1625
0.802721495 0.19802825 3133 0.904572565 0.2 1828
0.199033623 0.807009388 3522 0.914015905 0.2 1995
0.19934638 0.801593013 3576 0.947316103 0.2 1968
0.181085845 0.817494641 3422 0.857852883 0.2 1978
0.199723847 0.800314668 2818 0.959244533 0.2 1660
0.196035035 0.807669079 3474 0.935387674 0.2 1936
0.801170289 0.197894588 3123 0.900596421 0.2 1794
0.186789826 0.811825907 2346 0.941848907 0.2 1557
0.199418211 0.803792242 2892 0.877733598 0.2 1709
0.80114811 0.19897243 3123 0.893141153 0.2 1779
0.187909693 0.814625055 1462 0.967693837 0.2 1187
0.188264967 0.815196022 2366 0.922962227 0.2 1572
0.160821578 0.844725269 1462 0.948807157 0.2 1249
0.811675459 0.197301037 2635 0.5944334 0.2 1611
0.807768129 0.194833798 1721 0.924950298 0.2 1340
0.81672144 0.189905354 2721 0.692842942 0.2 1670
0.812509939 0.186515731 2613 0.902584493 0.2 1610
0.187626176 0.811146283 1890 0.965705765 0.2 1354
0.809093987 0.186732096 2879 0.784294235 0.2 1714
0.182467692 0.812978793 2224 0.902584493 0.2 1502
0.82281014 0.178912225 3417 0.884691849 0.2 1888
0.81072894 0.187464377 2509 0.919483101 0.2 1576
0.825353405 0.177710767 2077 0.96222664 0.2 1406
0.184201581 0.821954939 1890 0.960238569 0.2 1402
0.186205583 0.80964648 2202 0.922465209 0.2 1515
0.804104069 0.198380128 2119 0.887176938 0.2 1466
0.815940315 0.187692344 2401 0.94582505 0.2 1549
0.812589938 0.193009841 3393 0.757952286 0.2 1891
0.186376488 0.813656507 2596 0.913518887 0.2 1642
0.849356889 0.152046333 2635 0.784791252 0.2 1602
0.17215414 0.824281134 4092 0.934393638 0.2 2079
0.816009343 0.185068487 1517 0.892644135 0.2 1267
0.169892625 0.832135802 3150 0.903578529 0.2 1843
0.18425945 0.813187412 2224 0.85139165 0.2 1463
0.192665933 0.803601476 1552 0.942345924 0.2 1279
0.17548441 0.822830632 1468 0.944333996 0.2 1273
0.805694713 0.191837429 2635 0.897117296 0.2 1682
0.811624283 0.182526751 2077 0.928926441 0.2 1435
0.193804335 0.81091635 2030 0.977137177 0.2 1398
0.194974414 0.81605386 2116 0.900596421 0.2 1442
0.173520336 0.824645581 2224 0.905069583 0.2 1549
0.824025496 0.182606649 2537 0.893638171 0.2 1617
0.81157769 0.190398127 1529 0.944831014 0.2 1258
0.806934945 0.190069618 2333 0.928429423 0.2 1513
0.152767122 0.846780622 3766 0.858349901 0.2 1996
0.176046655 0.818509494 1664 0.953777336 0.2 1346
0.802991537 0.19546327 1905 0.932405567 0.2 1390
0.809308487 0.188290921 1155 0.894135189 0.2 1135
0.165343784 0.838606925 3526 0.869781312 0.2 1917
0.192920305 0.811343157 2596 0.903578529 0.2 1632
0.812329332 0.193576812 3027 0.847415507 0.2 1749
0.194248278 0.801305624 3952 0.862326044 0.2 2076
0.810031985 0.196998849 1529 0.957256461 0.2 1234
0.805353803 0.196460769 1913 0.956759443 0.2 1376
0.824920386 0.18113855 2879 0.766898608 0.2 1698
0.807870769 0.185390296 2883 0.904075547 0.2 1723
0.813212253 0.192204118 3181 0.785785288 0.2 1826
0.195677284 0.804696458 1940 0.862823062 0.2 1442
0.81960334 0.180103437 2049 0.955765408 0.2 1471
0.808136287 0.195731795 2411 0.748508946 0.2 1538
0.805292044 0.197273246 2613 0.917992048 0.2 1645
0.813949567 0.191539906 1913 0.89612326 0.2 1356
0.819350974 0.178694571 2389 0.944333996 0.2 1577
0.801869283 0.195756316 1641 0.924950298 0.2 1294
0.181123261 0.819830941 1908 0.9527833 0.2 1382
0.168042176 0.837226664 3150 0.890159046 0.2 1827
0.16905494 0.827902721 1890 0.941351889 0.2 1396
0.806482689 0.197313354 2227 0.88667992 0.2 1480
0.184081697 0.819854448 2224 0.92693837 0.2 1487
0.80108062 0.196985534 2145 0.930417495 0.2 1438
0.800530241 0.196415597 2213 0.931411531 0.2 1523
0.161971176 0.835970318 1802 0.956262425 0.2 1382
0.802824536 0.196755053 5285 0.533300199 0.2 2485
0.170431892 0.829537385 1664 0.96222664 0.2 1315
0.831851094 0.165521398 2263 0.769880716 0.2 1482
0.190280639 0.809631074 1908 0.935387674 0.2 1404
0.807757734 0.196089369 2651 0.839960239 0.2 1715
0.189348808 0.816040598 2892 0.924950298 0.2 1706
0.808014029 0.192119251 3049 0.865805169 0.2 1775
0.813446754 0.19156765 1641 0.885685885 0.2 1329
0.827124785 0.175320008 1353 0.826540755 0.2 1217
0.802275545 0.199196014 2021 0.953777336 0.2 1393
0.81918142 0.184982159 2623 0.848906561 0.2 1670
0.199217602 0.800000139 1802 0.942842942 0.2 1404
0.18523351 0.812737358 1664 0.962723658 0.2 1319
0.171128478 0.833322413 1802 0.953777336 0.2 1396
0.805884948 0.190636255 2651 0.827534791 0.2 1645
0.184978696 0.80938376 2224 0.923459245 0.2 1515
0.188861071 0.811225274 3876 0.927932406 0.2 2097
0.817882786 0.178492402 3905 0.912027833 0.2 2038
0.821244253 0.181385912 2623 0.714214712 0.2 1678
0.80748897 0.19313127 3487 0.852385686 0.2 1959
0.801602622 0.193248605 3181 0.953777336 0.2 1750
0.811370046 0.186820265 2119 0.876739563 0.2 1451
0.833128695 0.17321817 2109 0.916003976 0.2 1497
0.1762066 0.823275363 1552 0.960735586 0.2 1235
0.816269845 0.176690651 3441 0.706759443 0.2 1899
0.8053566 0.193802057 2613 0.935387674 0.2 1564
0.810192946 0.196067621 3089 0.94582505 0.2 1805
0.837325063 0.163132912 2635 0.663021869 0.2 1598
0.185052469 0.808999877 1952 0.946322068 0.2 1417
0.806969248 0.189263514 2119 0.880218688 0.2 1472
0.195466598 0.806896499 2022 0.931908549 0.2 1401
0.187369325 0.817699876 2366 0.968687873 0.2 1529
0.181193405 0.817569811 2832 0.954771372 0.2 1696
0.195825745 0.803327406 1664 0.968687873 0.2 1317
0.144099973 0.856266039 2832 0.897117296 0.2 1721
0.82903642 0.171177591 3417 0.854373757 0.2 1927
0.82622025 0.171688368 3219 0.738071571 0.2 1848
0.187125947 0.810636324 4614 0.894632207 0.2 2361
0.806789207 0.188366736 1721 0.90805169 0.2 1317
0.835223558 0.164203091 2109 0.873757455 0.2 1471
0.828910478 0.17241711 2191 0.870775348 0.2 1509
0.838924505 0.161694031 3905 0.877733598 0.2 2006
0.130601494 0.871066641 3150 0.94333996 0.2 1752
0.81714617 0.194117294 2521 0.934393638 0.2 1646
0.800730659 0.199974755 3085 0.729125249 0.2 1825
0.151126272 0.844345882 2596 0.93389662 0.2 1637
0.820793662 0.194142239 1353 0.781809145 0.2 1251
0.166527952 0.839230839 1890 0.951292247 0.2 1347
0.188388011 0.807875239 1946 0.943836978 0.2 1412
318052
0.091438335 0.909763262 3674 0.948807157 0.1 1943
0.093247802 0.906135942 1552 0.951789264 0.1 1243
0.087449738 0.912721441 2596 0.929920477 0.1 1646
0.901479326 0.097582244 2969 0.824055666 0.1 1773
0.098230741 0.900320699 2806 0.953777336 0.1 1677
0.909480742 0.088742015 2577 0.911530815 0.1 1603
0.903766086 0.096513956 2961 0.910536779 0.1 1807
0.067627874 0.932499802 3646 0.91749503 0.1 1996
0.919502454 0.082939245 2413 0.958747515 0.1 1586
0.921677169 0.074693445 2411 0.918986083 0.1 1560
0.913989345 0.087387393 2263 0.716699801 0.1 1526
0.919909985 0.080271052 3417 0.890656064 0.1 1919
0.921731771 0.075673264 2411 0.843439364 0.1 1561
0.914358466 0.090092533 3417 0.812127237 0.1 1939
0.089800625 0.909948824 3150 0.943836978 0.1 1766
0.05358602 0.948946849 3150 0.896620278 0.1 1868
0.914127258 0.086340442 2109 0.919483101 0.1 1415
0.90221684 0.091817851 2413 0.946819085 0.1 1564
0.923856401 0.077372246 1701 0.699304175 0.1 1397
0.077991216 0.920759513 3150 0.948807157 0.1 1836
0.092034129 0.905427379 3526 0.932902584 0.1 1955
0.09669537 0.904520301 2354 0.951292247 0.1 1539
0.090735909 0.912146679 4158 0.916998012 0.1 2110
0.086320731 0.912938644 2832 0.957256461 0.1 1716
0.906336925 0.089515876 2413 0.952286282 0.1 1549
0.071042961 0.927749081 3150 0.930417495 0.1 1786
0.088915181 0.911172144 4800 0.954771372 0.1 2383
0.908007969 0.089881197 3441 0.88667992 0.1 1873
0.906682454 0.098734144 3417 0.898111332 0.1 1884
0.907734388 0.091333334 4207 0.937375746 0.1 2193
0.099859521 0.900475876 3952 0.898111332 0.1 2101
0.900525343 0.099989851 2507 0.90805169 0.1 1571
0.091764795 0.906120389 3150 0.884194831 0.1 1901
0.080312059 0.919725438 3290 0.868787276 0.1 1808
0.905407532 0.093014393 2065 0.939363817 0.1 1440
0.074136854 0.928043261 3302 0.913021869 0.1 1872
0.90763293 0.089359743 2711 0.937872763 0.1 1604
0.086843572 0.911744021 3264 0.88916501 0.1 1930
0.08192054 0.919622652 2832 0.952286282 0.1 1746
0.904998308 0.093781861 2623 0.888170974 0.1 1590
0.906081271 0.096939708 2623 0.783797217 0.1 1640
0.088761558 0.914127387 1552 0.963717694 0.1 1262
0.095827551 0.907124081 3536 0.903578529 0.1 1929
0.93056749 0.07166667 2635 0.902087475 0.1 1622
0.077973399 0.921056017 3884 0.900099404 0.1 2053
0.910452348 0.087953628 2863 0.946819085 0.1 1732
0.917011754 0.080624947 2613 0.93389662 0.1 1607
0.075106401 0.924603842 4800 0.869781312 0.1 2375
0.903129547 0.096640611 2883 0.933399602 0.1 1697
0.088868453 0.913413712 2148 0.946322068 0.1 1466
0.907887897 0.092699446 2591 0.959741551 0.1 1592
0.098297885 0.900884451 1908 0.961232604 0.1 1416
0.084236457 0.915404934 2832 0.944831014 0.1 1692
0.904014584 0.098115462 2577 0.881212724 0.1 1591
0.911054547 0.089556444 2635 0.829025845 0.1 1616
0.097374232 0.906122088 1664 0.926441352 0.1 1289
0.915662642 0.087430986 2411 0.89612326 0.1 1575
0.064233492 0.93709005 2832 0.965705765 0.1 1729
0.907301119 0.095663996 2999 0.92445328 0.1 1718
0.900795629 0.096454267 2647 0.946322068 0.1 1669
0.937137998 0.060302473 3417 0.857852883 0.1 1945
0.902280095 0.096001192 2195 0.862326044 0.1 1466
0.904909179 0.095346491 2781 0.921968191 0.1 1673
0.909890363 0.088271597 2109 0.922465209 0.1 1491
0.900879311 0.097440493 3299 0.792743539 0.1 1865
0.082130793 0.915140659 1890 0.952286282 0.1 1357
0.914472523 0.087523774 3905 0.891650099 0.1 2079
0.058991378 0.941479538 3150 0.895129225 0.1 1774
0.91684018 0.082631005 2711 0.921471173 0.1 1656
0.092831069 0.907413275 3526 0.912524851 0.1 1912
0.928776969 0.070918449 2623 0.597912525 0.1 1635
0.096025157 0.903029283 3836 0.88667992 0.1 2024
0.087202578 0.914277144 2030 0.970675944 0.1 1455
0.066200861 0.930544579 2892 0.920974155 0.1 1687
0.084946115 0.912277472 2596 0.913021869 0.1 1589
0.075206995 0.924012949 2224 0.913518887 0.1 1491
0.903117843 0.097512211 3835 0.903081511 0.1 2040
0.098513085 0.900351699 2730 0.932902584 0.1 1649
0.90322684 0.09426548 2119 0.918986083 0.1 1484
0.923202218 0.079437435 2411 0.839960239 0.1 1566
0.097118535 0.901330223 2224 0.884691849 0.1 1551
0.914040023 0.086691229 4723 0.798707753 0.1 2325
0.906026275 0.095783075 2879 0.793240557 0.1 1668
0.077282421 0.923003135 2596 0.941351889 0.1 1657
0.091393404 0.908931519 4108 0.939363817 0.1 2074
0.911884724 0.086967543 2413 0.9527833 0.1 1544
0.904071494 0.094482004 2781 0.921968191 0.1 1669
0.911707784 0.09427911 2781 0.920477137 0.1 1715
0.098141753 0.901389144 2052 0.94333996 0.1 1429
0.902243259 0.096700564 2191 0.696322068 0.1 1490
0.085621291 0.915280018 1890 0.965208748 0.1 1385
0.083751087 0.912586675 2730 0.950298211 0.1 1646
0.071188323 0.9298519 1990 0.959244533 0.1 1438
0.927940605 0.069582082 2191 0.837972167 0.1 1490
0.906650169 0.095169293 2477 0.938866799 0.1 1605
0.927822583 0.070987326 3219 0.685387674 0.1 1850
0.093480296 0.907821814 5216 0.951789264 0.1 2501
0.930638982 0.065590531 2411 0.8444334 0.1 1601
0.909085939 0.090340698 4069 0.930914513 0.1 2083
0.094191433 0.904578579 2366 0.953280318 0.1 1509
0.921859516 0.079295739 2879 0.899602386 0.1 1713
0.92682286 0.074444818 2879 0.793240557 0.1 1714
0.074575091 0.925661523 1990 0.954771372 0.1 1419
0.912745586 0.087250646 3417 0.805666004 0.1 1940
0.901907466 0.099629939 3287 0.792246521 0.1 1858
0.901719433 0.097091757 3265 0.666998012 0.1 1864
0.907392839 0.093651172 2305 0.878230616 0.1 1490
0.061087599 0.939514172 3526 0.916998012 0.1 1887
0.081688723 0.91810876 2892 0.91500994 0.1 1738
0.90619687 0.093387191 2879 0.851888668 0.1 1712
0.903664532 0.098186209 3049 0.877236581 0.1 1835
0.913945845 0.088170582 3019 0.918489066 0.1 1778
0.918345405 0.081708217 2635 0.894135189 0.1 1591
0.900628897 0.098972701 2191 0.722664016 0.1 1481
0.938860635 0.059351565 2263 0.791252485 0.1 1533
0.926549882 0.072656292 2625 0.934890656 0.1 1637
0.098987417 0.904304283 2832 0.959741551 0.1 1697
0.08011271 0.918833947 2730 0.944333996 0.1 1633
0.086461947 0.913500569 2366 0.956759443 0.1 1504
0.911851965 0.087453743 2213 0.924950298 0.1 1450
0.907004432 0.091814729 2191 0.904075547 0.1 1491
0.90592292 0.093898772 1685 0.93638171 0.1 1317
0.093599422 0.904984556 2596 0.909542744 0.1 1654
0.095627239 0.900811682 1666 0.948807157 0.1 1302
0.089147145 0.909809086 3264 0.962723658 0.1 1883
0.907541737 0.094664818 4207 0.879224652 0.1 2131
0.092063872 0.907025241 2748 0.949304175 0.1 1656
0.925721446 0.07326217 2879 0.718687873 0.1 1718
0.076851472 0.921713703 3264 0.954274354 0.1 1889
0.901049034 0.0976087 4207 0.953777336 0.1 2183
0.084108204 0.916228202 3978 0.839463221 0.1 2083
0.906993413 0.089966259 2625 0.957256461 0.1 1683
0.097146422 0.90119489 3150 0.931908549 0.1 1806
0.951973635 0.051484301 2879 0.812127237 0.1 1694
0.07606907 0.922755127 7330 0.717693837 0.1 3252
0.916862756 0.084008276 4207 0.927932406 0.1 2146
0.91108049 0.09249275 2601 0.859343936 0.1 1706
0.08412513 0.913998232 3522 0.849900596 0.1 1958
0.908804367 0.09327816 2411 0.884194831 0.1 1549
0.07950068 0.921826781 1664 0.952286282 0.1 1290
0.903315686 0.098285797 4037 0.806163022 0.1 2063
0.096226022 0.90204302 2832 0.922465209 0.1 1666
0.908044005 0.094817264 2119 0.938866799 0.1 1475
0.906058632 0.095031584 3485 0.927435388 0.1 1921
0.908368371 0.093939089 2191 0.845427435 0.1 1479
0.083623581 0.916197976 3536 0.907554672 0.1 1954
0.092542539 0.908362121 4178 0.931908549 0.1 2205
0.08376605 0.918166795 3664 0.91749503 0.1 1957
0.90052018 0.098205131 2623 0.807157058 0.1 1676
0.94157011 0.061161754 3123 0.912524851 0.1 1806
0.09060908 0.909659448 2832 0.958747515 0.1 1684
0.907044979 0.090844033 2263 0.722664016 0.1 1527
0.086820079 0.910985286 3536 0.876739563 0.1 1965
0.909697722 0.088793284 2109 0.927932406 0.1 1451
0.906423853 0.096810281 1607 0.873757455 0.1 1256
0.906614098 0.094164219 3747 0.869284294 0.1 2031
0.902912484 0.096289741 3019 0.908548708 0.1 1738
0.088475745 0.910407754 2558 0.961729622 0.1 1584
0.90217198 0.094692717 4599 0.781809145 0.1 2299
0.902721635 0.093878309 4723 0.739562624 0.1 2361
0.09745529 0.904003364 3150 0.906560636 0.1 1838
0.906438401 0.09685707 2635 0.779821074 0.1 1674
0.904562009 0.096298886 3089 0.855864811 0.1 1828
0.090251852 0.91154452 3150 0.925447316 0.1 1804
0.072132967 0.929785331 3264 0.939860835 0.1 1863
0.902164749 0.097611016 3417 0.785785288 0.1 1864
0.914672577 0.084692877 2635 0.831013917 0.1 1626
0.919865592 0.08235439 2191 0.893141153 0.1 1510
0.902913617 0.09691792 2213 0.903578529 0.1 1468
0.902596035 0.095035604 4723 0.805168986 0.1 2360
0.924820818 0.077574011 2613 0.914512922 0.1 1662
0.083904157 0.914802765 3978 0.850894632 0.1 2128
0.916114547 0.081403281 3287 0.843936382 0.1 1844
0.091054205 0.906986474 1890 0.958747515 0.1 1395
0.905999362 0.093231 2119 0.939860835 0.1 1470
0.904211515 0.09273078 2853 0.801689861 0.1 1731
0.091692564 0.911701401 1890 0.946322068 0.1 1391
0.921433228 0.077606892 2263 0.702286282 0.1 1544
0.080489275 0.919428128 2730 0.935884692 0.1 1686
0.901876302 0.099498741 2625 0.939363817 0.1 1640
0.920254447 0.084076003 2119 0.959741551 0.1 1466
0.097482019 0.904799762 3830 0.912524851 0.1 2021
0.902149306 0.099257523 3417 0.831510934 0.1 1909
0.914966641 0.085379548 2853 0.883697813 0.1 1753
0.913781062 0.086698312 3545 0.89612326 0.1 1912
0.063868304 0.938135369 3260 0.930417495 0.1 1851
0.087842978 0.915515703 2366 0.97415507 0.1 1591
0.094849225 0.906849562 3956 0.955765408 0.1 2047
0.903245484 0.098126742 2145 0.937872763 0.1 1562
0.090492112 0.909397181 3260 0.909542744 0.1 1826
0.936584326 0.05994779 2635 0.772862823 0.1 1616
0.089245189 0.909119037 2832 0.944831014 0.1 1710
0.089754895 0.910148814 1780 0.960238569 0.1 1365
0.914625737 0.081111203 2227 0.941351889 0.1 1517
0.093587752 0.906978867 2148 0.949801193 0.1 1474
0.087619067 0.909770349 3854 0.815606362 0.1 2000
0.071304677 0.925174963 1990 0.946819085 0.1 1423
0.073369024 0.92238198 3526 0.924950298 0.1 1953
0.093973852 0.903211042 2022 0.934890656 0.1 1434
344265
0.005807882 0.994147492 3264 0.954771372 0.01 1839
0.992279261 0.007931055 4295 0.940854871 0.01 2202
0.994179988 0.005773797 2263 0.739562624 0.01 1562
0.99115566 0.008471334 4001 0.878727634 0.01 2085
0.993365612 0.006696313 5061 0.656560636 0.01 2464
0.00931579 0.990297521 3048 0.969681909 0.01 1793
0.992511981 0.007388838 4723 0.771371769 0.01 2363
0.009006401 0.990963818 4092 0.961232604 0.01 2180
0.990793782 0.009434084 2263 0.810139165 0.01 1494
0.990157042 0.009836295 4207 0.957256461 0.01 2138
0.005981661 0.993930791 3884 0.892644135 0.01 2100
0.009577105 0.990549691 2832 0.966202783 0.01 1729
0.991021869 0.009029182 4723 0.857355865 0.01 2309
0.991396789 0.008969281 3417 0.9527833 0.01 1877
0.007707252 0.99217051 3302 0.945328032 0.01 1840
0.990957693 0.008853194 5061 0.80417495 0.01 2508
0.0094395 0.990723407 2030 0.967196819 0.01 1441
0.990296846 0.009815455 3417 0.907554672 0.01 1854
0.991686918 0.008549641 2627 0.956759443 0.01 1654
0.993263925 0.006823684 3019 0.877236581 0.01 1761
0.004892927 0.995081822 3264 0.932902584 0.01 1846
0.008273287 0.991353376 3264 0.954771372 0.01 1889
0.005713532 0.994295506 5114 0.904075547 0.01 2404
0.006987704 0.993081267 4032 0.965208748 0.01 2075
0.005617351 0.994568391 3264 0.930417495 0.01 1887
0.991907844 0.007940426 3441 0.942345924 0.01 1889
0.99176369 0.008517901 3545 0.821073559 0.01 1914
0.99241283 0.007613923 3417 0.924950298 0.01 1878
0.008841042 0.991510757 4886 0.954771372 0.01 2406
0.005766109 0.994142591 3150 0.956759443 0.01 1848
0.991754325 0.008104551 4833 0.736580517 0.01 2377
0.990054059 0.009919383 3931 0.867296223 0.01 2108
0.991347181 0.008886795 4517 0.755467197 0.01 2204
0.008453219 0.991551498 3150 0.96222664 0.01 1892
0.008302311 0.992114853 3956 0.967196819 0.01 2061
0.009283473 0.990734829 3884 0.910039761 0.01 2031
0.991083112 0.008984886 3959 0.862326044 0.01 2119
0.007702694 0.992331992 3264 0.923459245 0.01 1888
0.990826469 0.009321522 6185 0.516898608 0.01 2758
0.993626956 0.006418925 2411 0.924950298 0.01 1605
0.008829138 0.991206177 3884 0.880218688 0.01 2022
0.009612568 0.990333682 3942 0.881709742 0.01 2116
0.991300334 0.00840903 2263 0.847912525 0.01 1483
0.006490538 0.993607644 4920 0.873757455 0.01 2483
0.990896502 0.009080058 2413 0.940357853 0.01 1564
0.006887905 0.993162132 3264 0.951789264 0.01 1829
0.990656732 0.009377136 4517 0.835984095 0.01 2298
0.990559956 0.00958641 2647 0.959244533 0.01 1648
0.993351124 0.00684683 5055 0.576540755 0.01 2410
0.990798624 0.009345369 4833 0.805168986 0.01 2399
0.004021785 0.996027833 3264 0.968190855 0.01 1820
0.009599344 0.990336762 7330 0.904075547 0.01 3171
0.007204229 0.992945252 4092 0.929920477 0.01 2176
0.005148893 0.995114079 3264 0.94333996 0.01 1886
0.991527367 0.008734194 3931 0.869284294 0.01 2052
0.009426728 0.990365697 5688 0.880715706 0.01 2613
0.992321629 0.007804665 2901 0.823558648 0.01 1828
0.992569213 0.007196136 4723 0.525347913 0.01 2329
0.993147901 0.007221452 2969 0.917992048 0.01 1789
0.990896781 0.008867339 3417 0.939363817 0.01 1921
0.990853212 0.009337063 2969 0.921471173 0.01 1729
0.008762343 0.991103461 3150 0.946819085 0.01 1850
0.99329582 0.006813113 2411 0.925944334 0.01 1587
0.008055558 0.992036753 4092 0.931908549 0.01 2122
0.008984521 0.990992958 3178 0.892147117 0.01 1786
0.990974492 0.008826378 4723 0.530318091 0.01 2372
0.990954926 0.009155371 3919 0.75 0.01 2051
0.008184082 0.991742407 4614 0.938866799 0.01 2281
0.992082571 0.00771109 4797 0.952286282 0.01 2325
0.991414966 0.008617977 3417 0.889662028 0.01 1967
0.009270146 0.990565372 4092 0.956759443 0.01 2136
0.003243768 0.996782695 3264 0.956759443 0.01 1919
0.992990079 0.00713258 3417 0.947316103 0.01 1940
0.994816333 0.005153132 4517 0.792743539 0.01 2276
0.991298434 0.008622996 2901 0.786779324 0.01 1696
0.992465782 0.007634446 4443 0.9055666 0.01 2279
0.993581904 0.006305667 5823 0.770874751 0.01 2763
0.992274717 0.007986899 3919 0.810139165 0.01 2083
0.005886462 0.994133882 3956 0.921968191 0.01 2100
0.007870846 0.992173079 3664 0.841451292 0.01 1983
0.990767893 0.009462385 3417 0.906063618 0.01 1862
0.008380061 0.99158031 2832 0.948807157 0.01 1706
0.008222762 0.991576519 3150 0.954771372 0.01 1902
0.008955578 0.991307543 3260 0.937872763 0.01 1836
0.990285253 0.009646381 4517 0.731610338 0.01 2301
0.00511816 0.99499422 3264 0.944333996 0.01 1812
0.992931614 0.006949766 2411 0.873757455 0.01 1524
0.991930087 0.008199743 2635 0.899602386 0.01 1617
0.990325135 0.009496599 4207 0.920477137 0.01 2215
0.009233299 0.990716182 3878 0.967693837 0.01 2087
0.008061717 0.991960653 4614 0.962723658 0.01 2274
0.004081447 0.99598976 4092 0.967196819 0.01 2089
0.005735921 0.994207388 3884 0.862823062 0.01 2112
0.991554133 0.008407168 2635 0.861829026 0.01 1632
0.990691836 0.008876126 5061 0.560636183 0.01 2448
0.990315854 0.009964386 3417 0.958747515 0.01 1905
0.007333355 0.992855446 3264 0.949801193 0.01 1884
0.00921207 0.990820662 3290 0.914015905 0.01 1903
0.990607666 0.009218021 4833 0.750497018 0.01 2413
0.004648328 0.995228963 3264 0.950298211 0.01 1806
0.006788124 0.993294394 3956 0.947813121 0.01 2102
0.003751713 0.996162768 3884 0.891650099 0.01 2092
0.991433481 0.00851344 2635 0.828031809 0.01 1630
0.991833741 0.008020297 3417 0.895626243 0.01 1942
0.00729723 0.992826701 3264 0.975646123 0.01 1855
0.991540388 0.008766854 4833 0.625248509 0.01 2397
0.991821655 0.007993984 2411 0.892147117 0.01 1607
0.008136354 0.992056147 3884 0.876739563 0.01 2045
0.007965661 0.991916283 3766 0.923459245 0.01 2052
0.0076707 0.992188955 2832 0.959244533 0.01 1727
0.990484054 0.00978636 4037 0.712723658 0.01 2091
0.991541289 0.008557112 2635 0.925944334 0.01 1648
0.007815367 0.992372428 3884 0.887176938 0.01 2081
0.009417868 0.990429289 4178 0.912524851 0.01 2152
0.994772809 0.005128878 5061 0.622763419 0.01 2445
0.990532319 0.009448051 4517 0.847912525 0.01 2266
0.009465812 0.990505707 3536 0.920974155 0.01 1933
0.990202747 0.009439905 3123 0.961232604 0.01 1898
0.008763177 0.991139672 3290 0.944333996 0.01 1861
0.005962824 0.994022534 3150 0.963717694 0.01 1777
0.008700842 0.991393509 4614 0.903578529 0.01 2239
0.991468631 0.00860948 2999 0.942842942 0.01 1794
0.00784714 0.992181957 9234 0.851888668 0.01 3865
0.991763569 0.008312608 4001 0.854373757 0.01 2121
0.008713858 0.99136985 5004 0.94582505 0.01 2448
0.990092738 0.009885944 3417 0.943836978 0.01 1891
0.002820865 0.997152501 4614 0.93638171 0.01 2328
0.009386496 0.990300925 3956 0.965705765 0.01 2130
0.991176583 0.008608241 3417 0.906560636 0.01 1953
0.007248752 0.992774385 3526 0.960238569 0.01 1912
0.004755968 0.995176115 3884 0.880218688 0.01 2024
0.007556302 0.992430382 3884 0.915506958 0.01 2100
0.009723805 0.990328592 3264 0.954771372 0.01 1914
0.993975076 0.006002315 4291 0.858846918 0.01 2178
0.990508024 0.009875654 2413 0.950795229 0.01 1592
0.991309652 0.008838517 3545 0.916003976 0.01 1928
0.992376854 0.007532802 6867 0.597415507 0.01 3054
0.006782796 0.99336332 4614 0.945328032 0.01 2327
0.990550851 0.009433004 3299 0.8444334 0.01 1885
0.991977992 0.007906704 4517 0.822067594 0.01 2299
0.008944165 0.990818092 4516 0.802186879 0.01 2275
0.994903037 0.005178879 4443 0.840954274 0.01 2251
0.990701797 0.009335398 3417 0.909045726 0.01 1877
0.007414705 0.992381582 4614 0.924950298 0.01 2328
0.992601225 0.007141488 2879 0.706262425 0.01 1679
0.009811136 0.990394208 3150 0.965208748 0.01 1853
0.992481609 0.007494196 4599 0.771371769 0.01 2306
0.990775293 0.00913833 4833 0.746023857 0.01 2393
0.006477841 0.99340967 3884 0.892644135 0.01 1997
0.99449471 0.005602172 4517 0.830516899 0.01 2255
0.007671963 0.992383501 3150 0.957753479 0.01 1738
0.990324994 0.009612908 5569 0.827037773 0.01 2615
0.993475921 0.006328596 5729 0.808151093 0.01 2773
0.008096849 0.991997572 3668 0.847415507 0.01 1950
0.00799623 0.992007902 3150 0.933399602 0.01 1752
0.005946171 0.994248711 3264 0.961729622 0.01 1876
0.005733945 0.994429109 4786 0.939363817 0.01 2354
0.006681551 0.993105858 3526 0.951292247 0.01 1935
0.9905429 0.009117635 2411 0.914015905 0.01 1545
0.991330346 0.008374624 5775 0.902584493 0.01 2754
0.993495203 0.006346148 2413 0.972664016 0.01 1529
0.006424894 0.993796073 3884 0.868290258 0.01 2008
0.990854809 0.008882425 5285 0.650596421 0.01 2563
0.99091496 0.008751393 4723 0.691351889 0.01 2324
0.007199282 0.992720891 4614 0.937872763 0.01 2272
0.993684128 0.006223434 4723 0.64612326 0.01 2310
0.996100355 0.003993674 5823 0.701292247 0.01 2735
0.991188247 0.008889304 3747 0.884194831 0.01 2031
0.00531102 0.994631344 3956 0.937872763 0.01 2073
0.990735659 0.009464418 4155 0.958747515 0.01 2087
0.9929749 0.007129667 5271 0.654075547 0.01 2584
0.008856627 0.991046321 3150 0.932405567 0.01 1846
0.005981678 0.993937948 3884 0.85139165 0.01 2102
0.991903882 0.008183649 2997 0.904572565 0.01 1806
0.990731472 0.009318552 4207 0.926441352 0.01 2138
0.992088894 0.007867443 2635 0.831510934 0.01 1587
0.008337119 0.991688862 4092 0.942345924 0.01 2209
0.991082358 0.009158951 2635 0.862823062 0.01 1650
0.99136024 0.008527193 2893 0.868787276 0.01 1734
0.991677979 0.008405772 3417 0.93389662 0.01 1907
0.991509579 0.008694674 2969 0.931411531 0.01 1761
0.992859066 0.007025714 5061 0.798707753 0.01 2483
0.008150092 0.992009026 4424 0.939363817 0.01 2195
0.003470646 0.996634116 3264 0.954274354 0.01 1917
0.991412419 0.008389824 2647 0.967693837 0.01 1673
0.00979553 0.990207984 3150 0.958747515 0.01 1825
0.006893442 0.993065856 4092 0.953777336 0.01 2165
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