%% 清空环境变量

warning off % 关闭报警信息

close all % 关闭开启的图窗

clear % 清空变量

clc % 清空命令行

%% 导入数据

res = xlsread('数据.xlsx');

%% 数据分析

num_size = 0.8; % 训练集占数据集比例

outdim = 3; % 最后一列为输出

num_samples = size(res, 1); % 样本个数

res = res(randperm(num_samples), :); % 打乱数据集（不希望打乱时，注释该行）

num_train_s = round(num_size * num_samples); % 训练集样本个数

f_ = size(res, 2) - outdim; % 输入特征维度

%% 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);

%% 数据平铺

p_train = double(reshape(p_train, f_, 1, 1, M));

p_test = double(reshape(p_test , f_, 1, 1, N));

t_train = double(t_train)';

t_test = double(t_test )';

%% 构造网络结构

layers = [