Python环境下基于Savitzky-Golay滤波和Transformer优化网络的multi-step水质预测模型算法运行环境为Python，执行基于Savitzky-Golay滤波和Transformer优化网络的multi-step水质预测模型。算法可迁移至金融时间序列，地震/微震信号，机械振动信号，声发射信号，电压/电流信号，语音信号，声信号，生理信号（ECG,EEG,EMG）等信号。from math import sqrtfrom sklearn.metrics import mean_squared_error,mean_absolute_error,r2_scorefrom prepare_data_External_input import get_dataloader,get_dataloader_shufflefrom Network import *from sklearn.preprocessing import MinMaxScalerimport pandas as pdfrom uti import plot_curve,plot_singleLineimport scipy.signal as sg