bp2_gd_m_alr_perbaikan.m

this code for backpropagation on matlab. with indonesian language

% backpropagation dengan batchmode momentum dan adaptive larning rate(learngdx)
clear;

% data input dan target
P=[0 1 2 1 10 12 -5 -8 -10 -15; 0 1 -1 6 3 -1 -2 2 -5 2];
T=[0 0 1 1 2 2 -1 -1 -2 -2];

% membangun jaringan feedforward
net=newff(minmax(P), [5 1], {'tansig' 'purelin'}, 'traingdx');


% set max epoch, goal learning rate, show step
net.trainParam.epochs = 1500;
net.trainParam.goal = 1e-3;
net.trainParam.max_perf_inc = 1.06;
net.trainParam.lr = 0.1;
net.trainParam.lr_inc = 1.2;
net.trainParam.lr_dec = 0.6;
net.trainParam.mc = 0.75;
net.trainParam.show = 100;

% melakukan pembelajaran
net = train(net,P,T)

%melihat bobot awal input lapisan, dan bias
bobotawal_input         = net.IW{1,1}
bobotawal_bias_input    = net.b{1,1}
bobotawal_lapisan       = net.LW{2,1}
bobotawal_bias_lapisan  = net.b{2,1}

% melakukan simulasi
y = sim(net,P)

% menggambar grafik
pause
subplot(211)
plot(P(1,:),T,'bo',P(1,:),y,'r*');
title('Perbandingan antara target (o) dan output jaringan (*)');
xlabel('input pertama');
ylabel('target atau ooutput');
grid;
subplot(212)
plot(P(2,:),T,'bo',P(2,:),y,'r*');
title('Perbandingan antara target (o) dan output jaringan (*)');
xlabel('input kedua');
ylabel('target atau ooutput');
grid;