標(biāo)題: 贈(zèng)MATLAB遺傳算法代碼 [打印本頁(yè)]
作者: lhjy    時(shí)間: 2019-5-4 02:45
標(biāo)題: 贈(zèng)MATLAB遺傳算法代碼
贈(zèng)MATLAB代碼與有緣人
  1. 遺傳算法

  3. function error = fun(x,inputnum,hiddennum,hiddennum,outputnum,net,inputn,outputn)
  4. x1 = x(1:inputnum*hiddennum);
  5. B1 = x(inputnum*hiddennum+1:inputnum*hiddennum+hiddennum);
  6. w2 = x(inputnum*hiddennum+hiddennum+1:inputnum*hiddennum+hiddennum+hiddennum*outputnum);
  7. B2 = x(inputnum*hiddennum+hiddennum+hiddennum*outputnum+1:inputnum*hiddennum+hiddennum+hiddennum*outputnum+outputnum);
  8. net.iw{1,1}=reshape(w1,hiddennum,inputnum);
  9. net.lw{2,1}=reshape(w2,outputnum,hiddennum);
  10. net.b{1}=reshape(B1,hiddennum,1);
  11. net.b{2}=B2;
  12. net=newff(inputn,outputn,hiddennum);
  13. net.trainParam.epochs=20;
  14. net.trainParam.lr=0.1;
  15. net.trainParam.goal=0.00001;
  16. net.trainParam.show=100;
  17. net.trainParam.showWindow=0;
  18. net=train(net,inputn,outputn);
  19. an=sim(net,inputn);
  20. error=sum(abs(an-outputn));

  22. 選擇操作

  24. function ret=select(individuals,sizepop)
  25. fitness1=10./individuals.fitness;
  26. sumfitness=sum(fitness1);
  27. sumf=fitmessl./sumfitness;
  28. index=[];
  29. for i=1:sizepop
  30.     pick=rand;
  31.     while pick==0
  32.         pick=rand;
  33.     end
  34.     for i=1:sizepop
  35.         pick=pick-sumf(i);
  36.         if pick<0
  37.             index=[index i];
  38.             break;
  39.         end
  40.     end
  41. end
  42. individuals.chrom=individuals.chrom(index,:);
  43. individuals.fitness=individuals.fitness(index);
  44. ret=individuals;

  46. 交叉操作

  48. function ret=Cross(pcross,lenchrom,chrom,sizepop,bound)
  49. for i=1:sizepop
  50.     pick=rand(1,2);
  51.     while prod(pick)==0
  52.         pick=rand(1,2);
  53.     end
  54.     index=ceil(pick.*sizepop);
  55.     pick=rand;
  56.     while pick==0
  57.         pick=rand;
  58.     end
  59.     if pick>pcross
  60.         continue;
  61.     end
  62.     flag=0;
  63.     while flag==0
  64.         pick=rand;
  65.     end
  66.     pos=ceil(pick.*sum(lenchrom));
  67.     pick=rand;
  68.     v1=chrom(index(1),pos);
  69.     v2=chrom(index(2),pos);
  70.     chrom(index(1),pos)=pick*v2+(1-pick)*v1;
  71.     chrom(index(2),pos)=pick*v1+(1-pick)*v2;
  72.     flag1=test(lenchrom,bound,chrom(index(1),:));
  73.     flag2=test(lenchrom,bound,chrom(index(2),:));
  74.     if flag1*flag2==0
  75.         flag=0;
  76.     else flag=1;
  77.     end
  78. end
  79. end
  80. ret=chrom;
  81.    


  84. 變異操作

  86. function ret=Mutation(pmutation,lenchrom,chrom,sizepop,num,maxgen,bound)
  87. for i=1:sizepop
  88.     pick=rand;
  89.     while pick==0
  90.         pick=rand;
  91.     end
  92.     index=ceil(pick*sizepop);
  93.     pick=rand;
  94.     if pick>pmutation
  95.         continue;
  96.     end
  97.     flag=0;
  98.     while flag==0
  99.         pick=rand;
  100.         while pick==0
  101.             pick=rand;
  102.         end
  103.         pos=ceil(pick*sum(lenchrom));
  104.         v=chrom(i,pos);
  105.         v1=v-bound(pos,1);
  106.         v2=bound(pos,2)-v;
  107.         pick=rand;
  108.         fg=(rand*(1-num/maxgen))^2;
  109.         if pick>0.5
  110.             chrom(i,pos)=chrom(i,pos)+(bound(pos,2)-chrom(i,pos))*fg;
  111.         else
  112.            chrom(i,pos)=chrom(i,pos)-(bound(i,pos)-bound(pos,1))*fg;
  113.         end
  114.         flag=test(lenchrom,boun,chrom(i,;));
  115.     end
  116. end
  117. ret=chrom;  

  119.             
  120.         
  121. 遺傳算法主函數(shù)

  123. clc
  124. clear
  125. load data input output
  126. inputnum=2;
  127. hiddennum=5;
  128. outputnum=1;
  129. input_train=input(1:1900,:)';
  130. input_test=input(1901:2000,:)';
  131. output_train=output(1:1900)';
  132. output_test=output(1901:2000)';
  133. [inputn,inputps]=mapminmax(input_train);
  134. [outputn,outputps]=mapminmax(output_train);
  135. net=newff(inputn,outputn,hiddennum);
  136. maxgen=50;
  137. sizepop=10;
  138. pcross=[0.4];
  139. pmutation=[0.2];
  140. numsum=inputnum*hiddennum+hiddennum+hiddennum*outputnum+outputnum;
  141. lenchrom=ones(1,numsum);
  142. bound=[-3*ones(numsum,1)3*ones(numsum,1)];
  143. individuals=struct('fitness',zeros(1,sizepop),'chrom',[]);
  144. avgfitness=[];
  145. bestfitness=[];
  146. bestchrom=[];
  147. for i=1:sizepop
  148.     individuals.chrom(i,:)=Code(lenchrom,bound);
  149.     x=individuals.chrom(i,:);
  150.     individuals.fitness(i)=fun(x,inputnum,hiddennum,outputnum,net,inputn,outputn);
  151. end
  152. for i=1:maxgen
  153.     individuals=Select(individuals,sizepop);
  154.     individuals.chrom=Cross(pcross,lenchrom,individuals.chrom,sizepop,i,maxgen,bound);
  155.     for j=1:sizepop
  156.         x=individuals.chrom(j,:);
  157.         individuals.fitness(j)=fun(x,inputnum,hiddennum,outputnum,net,inputn,output n);
  158.     end
  159.     [newbestfitness,newbestindex]=min(individuals.fitness);
  160.     [worestfitness,worestindex]=max(individuals.fitness);
  161.     if bestfitness>newbestfitness
  162.         bestfitness=newbestfitness;
  163.         bestchrom=individuals.chrom(newbestindex,:);
  164.     end
  165.     individuals.chrom(worestindex,:)=bestchrom;
  166.     individuals.fitness(worestindex,:)=bestfitness;
  167.     avgfitness=sum(individuals.fitness)/sizepop;
  168.     trace=[trace;avgfitness bestfitness];
  169. end

  171. 遺傳算法優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)函數(shù)擬合

  173. x=bestchrom
  174. x1=x(1:inputnum*hiddennum);
  175. B1=x(inputnum*hiddennum+1:inputnum*hiddennum+hiddennum);
  176. w2=x(inputnum*hiddennum+hiddennum+1;inputnum*hiddennum+hiddennum+hiddennum*outputnum);
  177. B2=x(inputnum*hiddennum+hiddennum+hiddennum*outputnum+1;inputnum*hiddennum+hiddennum+hiddennum*outputnum+outputnum);
  178. net.iw{1,1}=reshape(w1,hiddennum,inputnum);
  179. net.lw{2,1}=reshape(w2,outputnum,hiddennum);
  180. net.b{1}=reshape(B1,hiddennum,1);
  181. net.b(2)=B2;
  182. net.trainParam.epochs=100;
  183. net.trainParam.lr=0.1;
  184. [net,per2]=trian(net,inputn,outputn);
  185. inputn_test=mapminmax('apply',input_test,inputps);
  186. an=sim(net,inputn_test);
  187. test_simu=mapminmax('reverse',an,outputps);
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遺傳算法



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