多輸入多輸出 | MATLAB實現GWO-Elman灰狼優化循環神經網絡多輸入多輸出預測
目錄
- 多輸入多輸出 | MATLAB實現GWO-Elman灰狼優化循環神經網絡多輸入多輸出預測
- 預測效果
- 基本介紹
- 程序設計
- 往期精彩
- 參考資料
預測效果
基本介紹
Matlab實現GWO-Elman灰狼優化循環神經網絡多輸入多輸出預測
1.data為數據集,10個輸入特征,3個輸出變量。
2.main.m為主程序文件。
程序設計
- 完整程序和數據下載方式私信博主回復:Matlab實現GWO-Elman灰狼優化循環神經網絡多輸入多輸出預測。
%--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
%% 清空環境變量
warning off % 關閉報警信息
close all % 關閉開啟的圖窗
clear % 清空變量
clc % 清空命令行
%--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
%% 導入數據
res = xlsread('data.xlsx');
%-------------------------------------------------------------
%% 數據歸一化
[p_train, ps_input] = mapminmax(P_train, 0, 1);
p_test = mapminmax('apply', P_test, ps_input);
%--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
[t_train, ps_output] = mapminmax(T_train, 0, 1);
t_test = mapminmax('apply', T_test, ps_output);
%--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
%% 仿真測試
t_sim1 = sim(net, p_train);
t_sim2 = sim(net, p_test );
%--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
%% 數據反歸一化
T_sim1 = mapminmax('reverse', t_sim1, ps_output);
T_sim2 = mapminmax('reverse', t_sim2, ps_output);
往期精彩
MATLAB實現RBF徑向基神經網絡多輸入多輸出預測
MATLAB實現BP神經網絡多輸入多輸出預測
MATLAB實現DNN神經網絡多輸入多輸出預測
參考資料
[1] https://blog.csdn.net/kjm13182345320/article/details/126864256
[2] https://blog.csdn.net/kjm13182345320/article/details/126019698
[3] https://blog.csdn.net/kjm13182345320/article/details/125237445