2011年电工杯数学建模全国一等奖论文

output_train=input_test; output_test=output_test';

[inputn,inputps]=mapminmax(input_train); [outputn,outputps]=mapminmax(output_train);

net=newff(inputn,outputn,hiddennum);

maxgen=10; sizepop=10; pcross=[0.3]; pmutation=[0.1];

numsum=inputnum*hiddennum+hiddennum+hiddennum*outputnum+outputnum;

lenchrom=ones(1,numsum);

bound=[-3*ones(numsum,1) 3*ones(numsum,1)];

--------------------------------------------------

individuals=struct('fitness',zeros(1,sizepop), 'chrom',[]); avgfitness=[]; bestfitness=[]; bestchrom=[]; for i=1:sizepop

individuals.chrom(i,:)=Code(lenchrom,bound); x=individuals.chrom(i,:);

individuals.fitness(i)=fun(x,inputnum,hiddennum,outputnum,net,inputn,outputn);

end

[bestfitnessbestindex]=min(individuals.fitness);

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bestchrom=individuals.chrom(bestindex,:); avgfitness=sum(individuals.fitness)/sizepop; trace=[avgfitnessbestfitness];

for i=1:maxgen i

individuals=Select(individuals,sizepop); avgfitness=sum(individuals.fitness)/sizepop;

individuals.chrom=Cross(pcross,lenchrom,individuals.chrom,sizepop,bound);

individuals.chrom=Mutation(pmutation,lenchrom,individuals.chrom,sizepop,i,maxgen,bound);

for j=1:sizepop

x=individuals.chrom(j,:);

individuals.fitness(j)=fun(x,inputnum,hiddennum,outputnum,net,inputn,outputn);

end

[newbestfitness,newbestindex]=min(individuals.fitness); [worestfitness,worestindex]=max(individuals.fitness); ifbestfitness>newbestfitness bestfitness=newbestfitness;

bestchrom=individuals.chrom(newbestindex,:); end

individuals.chrom(worestindex,:)=bestchrom; individuals.fitness(worestindex)=bestfitness;

avgfitness=sum(individuals.fitness)/sizepop;

trace=[trace;avgfitnessbestfitness];

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end figure(1)

[r c]=size(trace);

plot([1:r]',trace(:,2),'b--'); x=bestchrom;

w1=x(1:inputnum*hiddennum);

B1=x(inputnum*hiddennum+1:inputnum*hiddennum+hiddennum); w2=x(inputnum*hiddennum+hiddennum+1:inputnum*hiddennum+hiddennum+hiddennum*outputnum);

B2=x(inputnum*hiddennum+hiddennum+hiddennum*outputnum+1:inputnum*hiddennum+hiddennum+hiddennum*outputnum+outputnum);

net.iw{1,1}=reshape(w1,hiddennum,inputnum); net.lw{2,1}=reshape(w2,outputnum,hiddennum); net.b{1}=reshape(B1,hiddennum,1); net.b{2}=B2;

net.trainParam.epochs=100; net.trainParam.lr=0.1;

[net,per2]=train(net,inputn,outputn);

inputn_test=mapminmax('apply',input_test,inputps); an=sim(net,inputn_test);

test_simu=mapminmax('reverse',an,outputps); error=test_simu-output_test;

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%适应度函数

function error =

fun(x,inputnum,hiddennum,outputnum,net,inputn,outputn)

w1=x(1:inputnum*hiddennum);

B1=x(inputnum*hiddennum+1:inputnum*hiddennum+hiddennum); w2=x(inputnum*hiddennum+hiddennum+1:inputnum*hiddennum+hiddennum+hiddennum*outputnum);

B2=x(inputnum*hiddennum+hiddennum+hiddennum*outputnum+1:inputnum*hiddennum+hiddennum+hiddennum*outputnum+outputnum);

net=newff(inputn,outputn,hiddennum); net.trainParam.epochs=20; net.trainParam.lr=0.1; net.trainParam.goal=0.00001; net.trainParam.show=100; net.trainParam.showWindow=0;

net.iw{1,1}=reshape(w1,hiddennum,inputnum); net.lw{2,1}=reshape(w2,outputnum,hiddennum); net.b{1}=reshape(B1,hiddennum,1); net.b{2}=B2;

net=train(net,inputn,outputn);

an=sim(net,inputn);

error=sum(abs(an-outputn));

%完成变异操作

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