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标题: [人工智能] 有没有神经网络实例，可以学习一下怎么编程？ [打印本页]

作者: 刘晓强 时间: 2013-8-16 09:28
标题: [人工智能] 有没有神经网络实例，可以学习一下怎么编程？

作者: 秦晓蕊 时间: 2013-8-16 09:35
clear%数据输入huanghe_p=[370503434575490420560640558343326405446423422697598377435472451667601689541485425389382707422];huanghe_t=[5157135867537205677179878104894535896395685959828495196156525999418939997587016305615201040 535];%归一化处理p=(huanghe_p-min(huanghe_p))/(max(huanghe_p)-min(huanghe_p));t=(huanghe_t-min(huanghe_t))/(max(huanghe_t)-min(huanghe_t));%数据输入2：网络有关参数EPOCHS=10000;GOAL=0.000005;%建立bp神经网络，并训练，仿真。其中输入为p，输出为t%-------------------------隐层神经元确定-----------------------------s=3:15;%s 为常向量，表示神经元的个数res=zeros(size(s));%res将要存储误差向量，这里先置零pn=[p(1:5);p(6:10);p(11:15);p(16:20)];tn=[t(1:5);t(6:10);t(11:15);t(16:20)];for i=1:length(s) net=newff(minmax(pn),[s(i),4],{&#39;tansig&#39;,&#39;purelin&#39;},&#39;trainlm&#39;); net.iw{1,1}=zeros(size(net.iw{1,1}))+0.5; net.lw{2,1}=zeros(size(net.lw{2,1}))+0.75; net.b{1,1}=zeros(size(net.b{1,1}))+0.5; net.b{2,1}=zeros(size(net.b{2,1})); net.trainParam.epochs=EPOCHS; net.trainParam.goal =GOAL; net=train(net,pn,tn); y=sim(net,pn);e=tn-y;error=mse(e,net);res(i)=norm(error);end%选取最优神经元数，number为使得误差最小的隐层神经元个数number=find(res==min(res));if(length(number)>1) no=number(1)else no=numberendclear error，res%选定隐层神经元数目后，建立网络，训练仿真。net=newff(minmax(pn),[no,4],{&#39;tansig&#39;,&#39;purelin&#39;},&#39;trainlm&#39;); net.iw{1,1}=zeros(size(net.iw{1,1}))+0.5; net.lw{2,1}=zeros(size(net.lw{2,1}))+0.75; net.b{1,1}=zeros(size(net.b{1,1}))+0.5; net.b{2,1}=zeros(size(net.b{2,1})); net.trainParam.epochs=EPOCHS; net.trainParam.goal =GOAL;net=train(net,pn,tn);y=sim(net,pn);e=tn-y;error=mse(e,net)%error为网络的误差向量r=norm(error);%r为网络的整体误差save net %保存最好的网络%预测input=[p(11:15);p(16:20);p(21:25);p(26:30)];yuce=sim(net,input);%结果反归一化y1=[y(1,

y(2,

y(3,

y(4,

];yuce1=[yuce(1,

yuce(2,

yuce(3,

yuce(4,

];t1=y1*(max(huanghe_t(1:20))-min(huanghe_t(1:20)))+min(huanghe_t(1:20));yuce2=yuce1*(max(huanghe_t(1:20))-min(huanghe_t(1:20)))+min(huanghe_t(1:20));%计算误差wucha=abs(t1-huanghe_t(1:20))./huanghe_t(1:20)b=minmax(wucha);average_wucha=mean(wucha);%作图figure(1)plot(1:20,huanghe_t(1:20),&#39;*-&#39;,1:20,t1,&#39;o:&#39;)figure(2)plot(1:20,huanghe_t(11:30),&#39;*-&#39;,1:20,yuce2,&#39;o:&#39;)

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