MAT之GA：GA優(yōu)化BP神經(jīng)網(wǎng)絡(luò)的初始權(quán)值、閾值，從而增強(qiáng)BP神經(jīng)網(wǎng)絡(luò)的魯棒性

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實現(xiàn)代碼

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實現(xiàn)代碼

global p global t global R global S1 global S2 global S S1 = 10;p = [0.01 0.01 0.00 0.90 0.05 0.00;0.00 0.00 0.00 0.40 0.50 0.00;0.80 0.00 0.10 0.00 0.00 0.00;0.00 0.20 0.10 0.00 0.00 0.10]'; t = [1.00 0.00 0.00 0.00;0.00 1.00 0.00 0.00;0.00 0.00 1.00 0.00;0.00 0.00 0.00 1.00]';P_test = [0.05 0 0.9 0.12 0.02 0.02;0 0 0.9 0.05 0.05 0.05;0.01 0.02 0.45 0.22 0.04 0.06;0 0 0.4 0.5 0.1 0;0 0.1 0 0 0 0]';net = newff(minmax(p),[S1,4],{'tansig','purelin'},'trainlm'); net.trainParam.show = 10; net.trainParam.epochs = 2000; net.trainParam.goal = 1.0e-3; net.trainParam.lr = 0.1;[net,tr] = train(net,p,t);s_bp = sim(net,P_test) R = size(p,1); S2 = size(t,1); S = R*S1 + S1*S2 + S1 + S2; aa = ones(S,1)*[-1,1];popu = 50; initPpp = initializega(popu,aa,'gabpEval',[],[1e-6 1]); gen = 100; [x,endPop,bPop,trace] = ga(aa,'gabpEval',[],initPpp,[1e-6 1 1],'maxGenTerm',gen,...'normGeomSelect',[0.09],['arithXover'],[2],'nonUnifMutation',[2 gen 3]);figure(1) plot(trace(:,1),1./trace(:,3),'r-'); title( 'GA優(yōu)化BP神經(jīng)網(wǎng)絡(luò)，繪制均方誤差變化曲線—Jason niu') hold on plot(trace(:,1),1./trace(:,2),'b-'); xlabel('Generation'); ylabel('Sum-Squared Error');figure(2) plot(trace(:,1),trace(:,3),'r-'); title( 'GA優(yōu)化BP神經(jīng)網(wǎng)絡(luò)，繪制適應(yīng)度函數(shù)變化曲線—Jason niu') hold on plot(trace(:,1),trace(:,2),'b-'); xlabel('Generation'); ylabel('Fittness');[W1,B1,W2,B2,val] = gadecod(x);net.IW{1,1} = W1; net.LW{2,1} = W2; net.b{1} = B1; net.b{2} = B2;net = train(net,p,t);s_ga = sim(net,P_test)

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GA：GA優(yōu)化BP神經(jīng)網(wǎng)絡(luò)的初始權(quán)值、閾值，從而增強(qiáng)BP神經(jīng)網(wǎng)絡(luò)的魯棒性
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