trainnerualnet.m

径向基神经网络训练程序

%%
% clear;
% load('Sample.mat');
p=[NNin,NNin,NNin,NNin,NNin,NNin,NNin,NNin,NNin,NNin];
t=[NNout,NNout,NNout,NNout,NNout,NNout,NNout,NNout,NNout,NNout];
[p,minp,maxp,t,mint,maxt]=premnmx(p,t);
% % net=newff(minmax(p),[30,2],{'tansig','purelin'},'trainlm');%  net=newcf(minmax(p),[45,25,8],{'tansig','tansig','purelin'},'trainlm');
net=newff(minmax(p),[30,2],{'tansig','tansig'},'trainlm');
net.trainParam.show=25;
net.trainParam.epochs = 250;
net.trainParam.goal = 1e-2;
%%
[net,tr]=train(net,p,t);
% save('080522');
NN2ManliangchengResult=sim(net,Faulttezheng(NN2FaulttestManliangcheng));
NN2JianfengResult=sim(net,Faulttezheng(NN2FaulttestJianfeng));
NNResult=sim(net,p);
% RTestResult=sim(net,RT);
% FTestResult=sim(net,FT);
% NNResult=sim(net,p);
% RTestResult=sim(net,RIGHTTesttezheng);
% FTestResult=sim(net,FAULTTESTtezheng);
% NNResult=sim(net,p);