file:gabp.m 
%************************************** 
clear all 
% 用GA訓(xùn)練BP網(wǎng)絡(luò)的權(quán)值、閾值 
% 開始計時 
tic, 
% BP網(wǎng)絡(luò)初始化 
[P,T,R,S1,S2,S]=bpinit; 
bounds=ones(S,1)*[-10 10]; 
% 初始種群個數(shù) 
num=60; 
pop=initializega(num,bounds,'fitness'); 

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
% clear all 
% % 用GA訓(xùn)練BP網(wǎng)絡(luò)的權(quán)值、閾值 
% % 開始計時 
% tic, 
% % BP網(wǎng)絡(luò)初始化 
% [P,T,R,S1,S2,S]=bpinit; 
% bounds=ones(S,1)*[0.1 0.9]; 
% % 初始種群個數(shù) 
% num=60; 
% pop=initializega(num,bounds,'fitness'); 
% % 遺傳代數(shù) 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 



% 遺傳代數(shù) 
gen=500; 
[x endPop bPop trace]=ga(bounds,'fitness',[],pop,[1e-6 1 1],'maxGenTerm',gen,... 
'normGeomSelect',[0.09],['arithXover'],[2],'nonUnifMutation',[2 gen 3]); 



for i=1:S 
  x(i)=endPop(1,i); 
end; 
sum=0; 
% 前R*S1個編碼為W1 
for i=1:S1, 
   for k=1:R, 
     W1(i,k)=x(R*(i-1)+k); 
   end 
end 
% 接著的S1*S2個編碼（即第R*S1個后的編碼）為W2 
for i=1:S2, 
  for k=1:S1, 
     W2(i,k)=x(S1*(i-1)+k+R*S1); 
  end 
end 
% 接著的S1個編碼（即第R*S1+S1*S2個后的編碼）為B1 
for i=1:S1, 
  B1(i,1)=x((R*S1+S1*S2)+i); 
end 
% 接著的S2個編碼（即第R*S1+S1*S2+S1個后的編碼）為B2 
for i=1:S2, 
  B2(i,1)=x((R*S1+S1*S2+S1)+i); 
end 
% 計算S1與S2層的輸出 
for i=1:100 
   x1=W1*P(i)+B1; 
   A1=1./(1+exp(-x1)); 
   x2=W2*A1+B2; 
   A2=1./(1+exp(-x2)); 
% A1=logsig(W1*P(1:17,i),B1); 
% A2=logsig(W2*A1,B2); 
YY(i)=A2; 
% 計算誤差平方和 
% SE=; 
%sum=sum+sumsqr(T(i)-A2); 
end 

i=1:1:100 
plot(i,YY(i),'r+',i,T(i),'b-'); 


% [W1 B1 W2 B2]=gadecod(x); 
% 仿真結(jié)果 
% TT=simuff(P,W1,B1,'logsig',W2,B2,'logsig') 
toc % 結(jié)束計時 

>>file:fitness.m 
function[sol,eval]=fitness(sol,options) 
[P,T,R,S1,S2,S]=bpinit; 
numv=size(sol,2)-1; 
       x=sol(1:numv); 
       eval=f(x); 

>>file:f.m 

function [eval]=f(sol) 
       numv=size(sol,2); 
       x=sol(1:numv); 
       [P,T,R,S1,S2,S]=bpinit; 
%get the value of fitness 

% 前R*S1個編碼為W1 
for i=1:S1 
   for k=1:R, 
     W1(i,k)=x(R*(i-1)+k); 
   end 
end 
% 接著的S1*S2個編碼（即第R*S1個后的編碼）為W2 
for i=1:S2 
  for k=1:S1, 
     W2(i,k)=x(S1*(i-1)+k+R*S1); 
  end 
end 
% 接著的S1個編碼（即第R*S1+S1*S2個后的編碼）為B1 
for i=1:S1 
  B1(i,1)=x((R*S1+S1*S2)+i); 
end 
% 接著的S2個編碼（即第R*S1+S1*S2+S1個后的編碼）為B2 
for i=1:S2 
  B2(i,1)=x((R*S1+S1*S2+S1)+i); 
end 


sum=0; 
SE=0; 
for i=1:100 
   x1=W1*P(i)+B1; 
   A1=1./(1+exp(-x1)); 
   x2=W2*A1+B2; 
   A2=1./(1+exp(-x2)); 
% A1=logsig(W1*P(1:17,i),B1); 
% A2=logsig(W2*A1,B2); 

% 計算誤差平方和 
SE=sumsqr(T(i)-A2); 
sum=sum+SE; 
end 
eval=10/sum; % 遺傳算法的適應(yīng)值 

>>file:bpinit.m 
% BP網(wǎng)絡(luò)初始化:給出網(wǎng)絡(luò)的訓(xùn)練樣本P、T, 
% 輸入、輸出數(shù)及隱含神經(jīng)元數(shù)R,S2,S1 
function [P,T,R,S1,S2,S]=bpinit; 
for i=1:100 
   P(i)=i; 
   T(i)=1/P(i); 
end 
[R,Q]=size(P);%R=1 
[S2,Q]=size(T);%S2=1 
S1=3;%3 nu 
S=R*S1+S1*S2+S1+S2; % 遺傳算法編碼長度