gabp.asv

关于遗传算法优化BP网络的 ,感觉没什么用

[P,T,R,S1,S2,Q,S]=nninit; % BP网络初始化
aa=ones(S,1)*[-1 1];
popu=60;
initPpp=initialize(popu,aa,'gabpEval');
gen=1000;
[x endPop bPop trace]=ga(aa,'gabpEval',[],initPpp,[1e-6 1 1],'maxGenTerm',gen,...
   'normGeomSelect',[0.09],['arithXover'],[2],'nonUnifMutation',[2 gen 3]);
subplot(2,1,1)
plot(trace(:,1),1./trace(:,3),'r-')
hold on
plot(trace(:,1),1./trace(:,2),'b-')
xlabel('Generation');
ylabel('Sum-Squared Error');
subplot(2,1,2)
plot(trace(:,1),trace(:,3),'r-')
hold on
plot(trace(:,1),trace(:,2),'b-')
xlabel('Generation');
ylabel('Fittness');
[W1 B1 W2 B2]=gadecod(x)

PP=[.347 .548 .738 .935 .54 1; .388 .577 .625 1 .8 1]';
% T1=sim(net,PP)
disp_fqre=100; max_epoch=30000;err_goal=0.001;lr=0.01;
 TP=[disp_fqre  max_epoch err_goal lr];
[W1,B1,W2,B2,te,tr]=trainbp(W1,B1,'tansig',W2,B2,'purelin',P,T,TP);
% 仿真结果
TT=simuff(PP,W1,B1,'tansig',W2,B2,'purelin')
T