基于python的LSTM时间序列预测

本文描述了，在污水数据背景下，利用长短期记忆神经网络对水质预测的方案。运行代码稳定可靠。

# No Pains,No Gains!
# @Time:2022/11/29 20:52

import numpy
import math
import keras
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from pandas import read_csv
import pandas as pd
from keras.models import Sequential
from tensorflow.keras import datasets
from keras.datasets import mnist
from keras.layers import Dense, Dropout, LSTM
from sklearn.preprocessing import StandardScaler, MinMaxScaler
from sklearn.metrics import mean_squared_error, mean_absolute_error
import tensorflow as tf
import os
import numpy as np
import seaborn as sns
from tensorflow import optimizers
from sklearn.model_selection import train_test_split

# 导入数据
dataframe = read_csv('nh4.csv', engine='python', skipfooter=0)

dataframe['date'] = pd.to_datetime(dataframe['date'])

dataset = dataframe['values'].values
dataset = numpy.array(dataset)

dataset.resize(len(