利用GA算法优化BP网络的权值和阈值进行预测

%--尝试建立用遗传算法优化bp网络权值和阈值，改善bp网络的性能 clc; clear all; close all; tic; %----初始化bp网络和遗传算法的相关系数 [P,T,inputs,helay,outputs,GenLength]=bpinit; popsize=60;%种群大小 P_cross=0.3;%交叉概率 P_muta=0.09;%变异概率 ecope=200;%遗传代数 chrom=initpop(popsize,GenLength);%初始化种群 k=1; c_value=1; %-----遗传操作 % while(c_value<10) while k <= ecope %保存最好的个体%-----初始化种群 %-----计算种群个体适应值 genefit=fitness(chrom,P,T,inputs,helay,outputs); [c_value index]=min(genefit); current_best(k,:)=chrom(index,:); current_bvalue(k)=c_value; % if c_value < 8.0 %selecting fit=cumsum(genefit)/(sum(genefit)); select_index=select(fit,popsize); selectchrom=chrom(select_index,:); %crossing P_c=rand(1,popsize); c_index=find(P_c<P_cross); crosschrom=selectchrom(c_index,:); crosschrom=cross(crosschrom); selectchrom(c_index,:)=crosschrom; %mutation mu_chrom=mutation(selectchrom,P_muta,popsize,ecope); chrom=mu_chrom; % else % break; % end k=k+1; %%caculate fitness value after mutation % genefit=fitness(chrom,P,T,inputs,helay,outputs); % [c_value index]=max(genefit); % fit=cumsum(genefit)/(sum(genefit)); % select_index=select(fit,popsize-1); % if c_value < current_bvalue(k) % chrom=[chrom(select_index,:);current_best(k,:)]; % genefit=[genefit(select_index(:)),current_bvalue(k)]; % else % select_index=[select_index index]; % chrom=chrom(select_index,:); % genefit=genefit(select_index); % end end % end [c_value index]=min(genefit); % w_he=[chrom(index,1:10);chrom(index,11:20);chrom(index,21:30)]'; % b_he=[chrom(index,31:40)]'; % w_out=[chrom(index,41:50);chrom(index,51:60);chrom(index,61:70)]; % b_out=[chrom(index,71:73)]'; [w_he,w_out,b_he,b_out]=gadecode(chrom(index,:),inputs,outputs,helay); net=newff(minmax(P),[helay outputs],{'logsig' 'logsig'},'traingd','learngd','sse'); net.iw{1,1} = w_he; net.b{1} =b_he; net.lw{2,1} = w_out; net.b{2} = b_out; net.trainParam.goal=0.01; net.trainParam.lr=0.6; net.trainParam.epochs=5000; net=init(net); [net,tr]=train(net,P,T); % tt=simuff(P,w_he,b_he,'logsig',w_out,b_out,'logsig'); tt=sim(net,P) error=tt-T; [m,n]=size(T); i=0:0.25:2*pi; plot(i,0,'b-',i,T,'r',i,tt,'k',i,error,'g'); grid; title('GA-BP'); toc