回归预测 | Matlab实现DE-BP差分算法优化BP神经网络多变量回归预测

目录

回归预测 | Matlab实现DE-BP差分算法优化BP神经网络多变量回归预测效果一览基本介绍程序设计参考资料

效果一览

基本介绍

1.Matlab实现DE-BP差分算法优化BP神经网络多变量回归预测（完整源码和数据） 2.运行环境为Matlab2018b； 3.excel数据集，输入多个特征，输出单个变量，多变量回归预测预测，DE_BP.m为主程序，运行即可,所有文件放在一个文件夹； 4.输出优化前后对比图，误差对比图； 代码特点：参数化编程、参数可方便更改、代码编程思路清晰、注释明细。

程序设计

完整源码和数据获取方式(资源处下载)：Matlab实现DE-BP差分算法优化BP神经网络多变量回归预测。

%% 清空环境变量

%选连样本输入输出数据归一化

[inputn,inputps]=mapminmax(input_train);

[outputn,outputps]=mapminmax(output_train);

%构建网络

net=newff(inputn,outputn,hiddennum);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%优化前的BP

net.trainParam.epochs=100;

net.trainParam.lr=0.1;

net.trainParam.goal=0.00001;

[net,~]=train(net,inputn,outputn);

inputn_test=mapminmax('apply',input_test,inputps);

an=sim(net,inputn_test);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%% 利用差分进化算法选择最佳的BP参数

D=inputnum*hiddennum+hiddennum+hiddennum*outputnum+outputnum;%变量个数%变量的维数

NP=5; %个体数目

G=30; %最大进化代数

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Xs=1*ones(D,1); %上限

Xx=-1*ones(D,1); %下限

%%%%%%%%%%%%%%%%%%%%%%%%%赋初值%%%%%%%%%%%%%%%%%%%%%%%%

xx=zeros(D,NP); %初始种群

v=zeros(D,NP); %变异种群

u=zeros(D,NP); %选择种群

xchu=rand(D,NP);

for i=1:NP

xx(:,i)=xchu(:,i).*(Xs-Xx)+Xx; %赋初始种群初值

end

%%%%%%%%%%%%%%%%%%%%计算目标函数%%%%%%%%%%%%%%%%%%%%%%%

trace(1)=min(Ob);

gbest=100;

%%%%%%%%%%%%%%%%%%%%%%%差分进化循环%%%%%%%%%%%%%%%%%%%%%

for gen=1:G

%%%%%%%%%%%%%%%%%%%%%%变异操作%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%r1,r2,r3和m互不相同%%%%%%%%%%%%%%%

for m=1:NP

r1=randi([1,NP],1,1);

while (r1==m)

r1=randi([1,NP],1,1);

end

r2=randi([1,NP],1,1);

while (r2==m)||(r2==r1)

r2=randi([1,NP],1,1);

end

r3=randi([1,NP],1,1);

while (r3==m)||(r3==r1)||(r3==r2)

r3=randi([1,NP],1,1);

end

v(:,m)=xx(:,r1)+F*(xx(:,r2)-xx(:,r3));

end

%%%%%%%%%%%%%%%%%%%%%%交叉操作%%%%%%%%%%%%%%%%%%%%%%%

r=randi([1,D],1,1);

for n=1:D

cr=rand(1);

if (cr<=CR)||(n==r)

u(n,:)=v(n,:);

else

u(n,:)=xx(n,:);

end

end

%%%%%%%%%%%%%%%%%%%边界条件的处理%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%边界吸收%%%%%%%%%%%%%%%%%%%%%%%%%

for n=1:D

for m=1:NP

if u(n,m)

u(n,m)=Xx(n);

end

if u(n,m)>Xs(n)

u(n,m)=Xs(n);

end

end

end

%%%%%%%%%%%%%%%%%%%%%%选择操作%%%%%%%%%%%%%%%%%%%%%%%

for m=1:NP

Ob1(m)=fitness(u(:,m));

end

for m=1:NP

if Ob1(m)

xx(:,m)=u(:,m);

end

end

for m=1:NP

Ob(m)=fitness(xx(:,m));

end

fbest=min(Ob);

if(fbest

gbest=fbest;

histor(gen)=fbest;

else

histor(gen)=gbest;

end

end

参考资料

[1] https://blog.csdn.net/kjm13182345320/article/details/129215161 [2] https://blog.csdn.net/kjm13182345320/article/details/128105718

参考链接

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