n=7;
x=[0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8];
y=[0.1 0.1 0.13 0.15 0.2 0.22 0.27 0.34 0.4 0.49 0.57 0.65 0.69 0.79 0.82 0.9 0.94];
p=[0 0.8 1;0.05 0.8 1;0.1 0.8 1;0.15 0.8 1;0.2 0.8 0.9;0.25 0.8 0.9;0.3 0.8 0.8]';
t=[0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.5 0.6 0.7 0.7 0.8 0.8 0.9 0.9 1 1;
    0 0.1 0.1 0.2 0.3 0.4 0.4 0.5 0.6 0.6 0.7 0.8 0.8 0.9 0.9 1 1;
    0 0 0.1 0.1 0.2 0.2 0.3 0.4 0.4 0.5 0.6 0.7 0.7 0.8 0.8 0.9 1;
    0 0 0 0.1 0.1 0.2 0.3 0.4 0.4 0.5 0.6 0.7 0.7 0.8 0.8 0.9 1;
    0 0 0 0 0.1 0.1 0.2 0.2 0.3 0.4 0.5 0.5 0.6 0.7 0.8 0.9 0.9;
    0 0 0 0 0 0.1 0.2 0.2 0.3 0.4 0.5 0.6 0.6 0.7 0.8 0.8 0.9;
    0 0 0 0 0 0 0.1 0.2 0.2 0.3 0.4 0.5 0.6 0.7 0.7 0.8 0.8]';
a=[0.15 0.75 1]';
net=newff(minmax(p),[n,17],{'tansig' 'purelin'},'trainlm');
net.trainParam.epochs=50;
net.trainParam.goal=0.01;
net=train(net,p,t);
y1=sim(net,a);
figure(1);
plot(x,y,'r--',x,y1);
axis([0 0.8 0 1]);
grid;
title('訓(xùn)練后的BP網(wǎng)絡(luò)仿真結(jié)果');
xlabel('制冷環(huán)境溫度A');
ylabel('輸出頻率及電壓F/U');