【源码】蜜蜂CNN进化算法

Bees CNN Algorithm (A Fuzzy Evolutionary Deep Leaning) - Created in 20 Jan 2022 by Seyed Muhammad Hossein Mousavi

% It is possible to fit deep learning weights and bias using evolutionary % algorithm, right after training stage. Here, CNN is used to classify 8 % face classes. After CNN train, initial fuzzy model is created to aid the % learning process. Finally, CNN network weights (from Fully Connected Layer) % trains using Bees algorithm % to be fitted in a nature inspired manner (here behavior of Bees). You can % used your data with any number of samples and classes. Remember, code’s % parameters are adjusted for this data and if you want to replace your % data you may have to change the parameters. Image data is in 64*64 size and % in 2 dimensions and stored in ‘CNNDat’ folder. So, important parameters % are as below: % 1. % ‘numTrainFiles’ = you have to change this based on number of your samples % in each class. for example if each class has 120 sample, 90 is good % enough as 90 samples considered for train and others for test. % 2. % ‘imageInputLayer’ = it is size of your image data like [64 64 1] % 3. % ‘fullyConnectedLayer’ = it is number of your classes like (8) % 4. % ‘MaxEpochs’ = the more the better and more computation run time like 40 % 5. % ‘ClusNum’ = Fuzzy C Means (FCM) Cluster Number like 3 or 4 is nice % 6. % These two are from “BEEFCN.m” function : % ‘Params.MaxIt’ = it is iteration number in Bees algorithm. 20 is good % ‘Params.nScoutBee’ = it is population number in Bees algorithm. Like 10. % ------------------------------------------------ % Feel free to contact me if you find any problem using the code:

% Author: SeyedMuhammadHosseinMousavi

% My Email: [email protected]

下载地址：

https://url92.ctfile.com/f/1850492-538768642-abc4ea

（访问密码：3660）