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ÎÒÓÃpsoÓÅ»¯bpÉñ¾­ÍøÂçÆäÖÐÐÞ¸Äʱ£¬³öÏÖÎÊÌâ²»ÖªµÀÔõôÐÞ¸ÄÊÊÓ¦¶ÈÖµº¯Êý£º function error = fun(x,inputnum,hiddennum,outputnum,net,inputn,outputn) %¸Ãº¯ÊýÓÃÀ´¼ÆËãÊÊÓ¦¶ÈÖµ %x          input     ¸öÌå %inputnum   input     ÊäÈë²ã½ÚµãÊý %outputnum  input     Òþº¬²ã½ÚµãÊý %net        input     ÍøÂç %inputn     input     ÑµÁ·ÊäÈëÊý¾Ý %outputn    input     ÑµÁ·Êä³öÊý¾Ý %error      output    ¸öÌåÊÊÓ¦¶ÈÖµ %ÌáÈ¡ 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); %ÍøÂç½ø»¯²ÎÊý net.trainParam.epochs=20; net.trainParam.lr=0.1; net.trainParam.goal=0.00001; net.trainParam.show=100; net.trainParam.showWindow=0; %ÍøÂçȨֵ¸³Öµ 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}=reshape(B2,outputnum,1); %ÍøÂçѵÁ· net=train(net,inputn,outputn); an=sim(net,inputn); error=sum(abs(an-outputn)); Ö÷º¯Êý %½Úµã¸öÊý inputnum=20; hiddennum=60; outputnum=5; %¹¹½¨ÍøÂç net=newff(inputn,outputn,hiddennum); % ²ÎÊý³õʼ»¯ %Á£×ÓȺËã·¨ÖеÄÁ½¸ö²ÎÊý c1 = 1.49445; c2 = 1.49445; maxgen=100;   % ½ø»¯´ÎÊý   sizepop=30;   %ÖÖȺ¹æÄ£ Vmax=1; Vmin=-1; popmax=5; popmin=-5; for i=1:sizepop     pop(i,=5*rands(1,1565);     V(i,=rands(1,21);     fitness(i)=fun(pop(i,,inputnum,hiddennum,outputnum,net,inputn,outputn); end % ¸öÌ弫ֵºÍȺÌ弫ֵ [bestfitness bestindex]=min(fitness); zbest=pop(bestindex,;   %È«¾Ö×î¼Ñ gbest=pop;    %¸öÌå×î¼Ñ fitnessgbest=fitness;   %¸öÌå×î¼ÑÊÊÓ¦¶ÈÖµ fitnesszbest=bestfitness;   %È«¾Ö×î¼ÑÊÊÓ¦¶ÈÖµ %% µü´úÑ°ÓÅ for i=1:maxgen     i;     for j=1:sizepop         %ËٶȸüР        V(j, = V(j, + c1*rand*(gbest(j, - pop(j,) + c2*rand*(zbest - pop(j,);         V(j,find(V(j,>Vmax))=Vmax;         V(j,find(V(j,<Vmin))=Vmin;         %ÖÖȺ¸üР        pop(j,=pop(j,+0.2*V(j,;         pop(j,find(pop(j,>popmax))=popmax;         pop(j,find(pop(j,<popmin))=popmin;         %×ÔÊÊÓ¦±äÒì         pos=unidrnd(21);         if rand>0.95             pop(j,pos)=5*rands(1,1);         end         %ÊÊÓ¦¶ÈÖµ         fitness(j)=fun(pop(j,,inputnum,hiddennum,outputnum,net,inputn,outputn);     end     for j=1:sizepop     %¸öÌå×îÓŸüР    if fitness(j) < fitnessgbest(j)         gbest(j, = pop(j,;         fitnessgbest(j) = fitness(j);     end     %ȺÌå×îÓŸüР    if fitness(j) < fitnesszbest         zbest = pop(j,;         fitnesszbest = fitness(j);     end     end     yy(i)=fitnesszbest;    end %% ½á¹û·ÖÎö plot(yy) title(['ÊÊÓ¦¶ÈÇúÏß  ' 'ÖÕÖ¹´úÊý£½' num2str(maxgen)]); xlabel('½ø»¯´úÊý');ylabel('ÊÊÓ¦¶È'); x=zbest; %% °Ñ×îÓųõʼ·§ÖµÈ¨Öµ¸³ÓèÍøÂçÔ¤²â % %ÓÃÒÅ´«Ëã·¨ÓÅ»¯µÄBPÍøÂç½øÐÐÖµÔ¤²â 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.trainParam.goal=0.00001; ²»ÖªµÀÊÊÓ¦¶ÈÖµº¯ÊýÔõôÐÞ¸ÄÀÏÊdzöÏÖÎÊÌâ Error using fun (line 13) Not enough input arguments.

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