plotresult.m

基于遗传算法对rbf神经网络的径向基宽度进行优化的matlab程序

load DATA01
load REALMFR1
Set=[a210a' f130a' f141a' t210' p210' l210' f211' f213' f217' realmfr1];
Gset=Set(77:85,:);
Set(77:85,:)=[];
VerifySet=Set(1:4:76,:);%验证集  19个样本
Set(1:4:76,:)=[];
TrainSet=Set;%训练集  57个样本

TrainX=TrainSet(:,1:9);
TrainY=TrainSet(:,10);

VerX=VerifySet(:,1:9);
VerY=VerifySet(:,10);

%训练
[pn meanp stdp]=prestd(TrainX');      %数据标准化
[pca,transmat]=prepca(pn,0.05);       %主元分析，提取95%的方差

%数据标准化
[R C]=size(VerX);
for i=1:R                          
pn2(:,i) = (VerX(i,:)'-meanp)./stdp;   
end

pca2=transmat*pn2;  %验证数据的主元提取     

net=newrb(pca,TrainY',0.01,Chrom(I));      %训练神经网络
V=sim(net,pca2);   %验证数据的输出

figure(2)
t=1:19;
plot(t,VerY,'-ro',t,V,'--g*')
%set(gca,'Ylim',[0,10])
legend('Analysis','Test')

d1 =max(abs(V-VerY'))
 md1=mean(abs(V-VerY')) 
     d2=max(abs(V-VerY')./VerY')
    md2=mean(abs(V-VerY')./VerY')
rm=rmse(V-VerY')