test.m

用RBF人工神经网络的智能算法,实现预测功能

X=(-pi:0.1:pi)'
Y=sin(X)
gam = 10;
sig2 = 0.3;
type = 'function estimation';
[alpha,b] = trainlssvm({X,Y,type,gam,sig2,'RBF_kernel'});
[alpha,b] = trainlssvm({X,Y,type,gam,sig2,'RBF_kernel','original'});
[alpha,b] = trainlssvm({X,Y,type,gam,sig2,'RBF_kernel','preprocess'});
Xt=(-pi:0.1:pi)'
Yt = simlssvm({X,Y,type,gam,sig2,'RBF_kernel','preprocess'},{alpha,b},Xt);
figure; plotlssvm({X,Y,type,gam,sig2,'RBF_kernel','preprocess'},{alpha,b});
hold on;  plot(Xt,Yt,'r-.'); hold off
nb=length(Xt)
Yp = predict({X,Y,type,gam,sig2}, Xt, nb)
hold on;  plot(Xt,Yp,'b-.'); hold off