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回归预测 | MATLAB实现GRNN广义回归神经网络多输入多输出预测

预测效果

基本介绍

MATLAB实现GRNN广义回归神经网络多输入多输出预测，输入10个特征，输出3个变量,程序乱码是由于版本不一致导致，可以用记事本打开复制到你的文件，运行环境MATLAB2018b及以上。
命令窗口输出MAE和R2，可在下载区获取数据和程序内容。

程序设计

• 完整程序和数据下载方式(资源处直接下载)：MATLAB实现GRNN广义回归神经网络多输入多输出预测

%-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
%%  划分训练集和测试集
P_train = res(1: num_train_s, 1: f_)';
T_train = res(1: num_train_s, f_ + 1: end)';
M = size(P_train, 2);
%-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
P_test = res(num_train_s + 1: end, 1: f_)';
T_test = res(num_train_s + 1: end, f_ + 1: end)';
N = size(P_test, 2);
%-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
%%  数据归一化
[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);————————————————
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往期精彩

MATLAB实现RBF径向基神经网络多输入多输出预测
MATLAB实现BP神经网络多输入多输出预测
MATLAB实现DNN神经网络多输入多输出预测
MATLAB实现LSTM长短期记忆神经网络多输入多输出预测

参考资料

[1] https://blog.csdn.net/kjm13182345320/article/details/116377961
[2] https://blog.csdn.net/kjm13182345320/article/details/127931217
[3] https://blog.csdn.net/kjm13182345320/article/details/127894261