我用GA程序优化40-15-3的神经网络，结果显示错误
??? Error using ==> network.subsasgn at 551
net.b{2} must be a 3-by-1 matrix.

Error in ==> fun at 30
net.b{2}=B2;
以下是代码：
clc
clear
%网络结构
inputnum=40;
hiddennum=15;
outputnum=3;
%读取数据
p=xlsread('network.xlsx','sheet3');
t=xlsread('network.xlsx','sheet4');
input_train=[p(:,1:11),p(:,15)];
input_test=p(:,12:14);
output_train=[t(:,1:11),t(:,15)];
output_test=t(:,12:14);
%数据归一化
[input1,ps]=mapminmax(input_train);
input2=mapminmax('apply',input_test,ps);
%建立网络
net=newff(input1,output_train,15);
%遗传算法参数初始化
maxgen=50
%迭代次数
sizepop=10
%种群规模
pcross=[0.4]
%交叉概率
pmutation=[0.2]
%变异概率
%节点总数
numsum=inputnum*hiddennum+hiddennum+hiddennum*outputnum+outputnum;


lenchrom=ones(1,numsum);
%个体长度
bound=[-3*ones(numsum,1) 3*ones(numsum,1)];
%个体范围
%种群信息定义为结构体
individuals=struct('fitness',zeros(1,sizepop),'chrom',[]);
avgfitness=[];
%每代平均适应度值
bestfitness=[];
%每代最佳适应度值
bestchrom=[];
%最优个体


%计算个体适应度值
for i = 1:sizepop

%个体初始化


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

%计算个体适应度值

x=individuals.chrom(i,:);

individuals.fitness(i)=fun(x,inputnum,hiddennum,outputnum,net,input1,output_train);
end
%迭代寻优
for i =1:maxgen

%选择操作

individuals=select(individuals.sizepop);

%交叉操作

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

%变异操作

individuals.chrom=mutation(pmutation,lenchrom,individuals.chrom,sizepop,I,maxgen,bound);

%计算适应度值

for j=1:sizepop

x=individuals.chrom(j,:);
%个体

individuals.fitness(j)=fun(x,inputnum.hiddennum,outputnum,net,input1,output_train);

end

%寻找最优最差个体

[newbestfitness,newbestindex]=min(individuals.fitness);

[worestfitness,worestindex]=max(individuals.fitness);

%最优个体更新

ifbestfitness>newbestfitness

bestfitness=newbestfitness;

bestchrom=individuals.chrom(newbestindex,:);

end

individuals.chrom(worestindex,:)=bestchrom;

individuals.fitness (worestindex)=bestfitness;

%记录最优个体适应度值和平均适应度值

avgfitness=sum(individuals.fitness)/sizepop;

trace=[trace;avgfitness bestfitness];
end


%把最优个体x赋给BP神经网络权值和阀值
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;
%BP神经网络参数
net.trainparam.epochs=100;
net. trainparam.lr=0.1;
net. trainparam.goal=0.00001;
%BP神经网络训练
net= train(net,input1,output_train);
%BP神经网络预测
an=sim(net,input_test);


%%预测结果归一化
test=mapminmax(‘reverse’,an,outputps);

我看了好几遍，也不知道究竟是哪里出错，能不能请高手帮我看看？
祝学习进步，工作顺利！！