bp_networkpredict.m

在matlab环境下的BP网络预测程序

p=[12000 0.5 0.05 2.0 5  0.025 1;
   12000 1.5 0.20 4.0 15 0.050 2;
   12000 2.5 0.35 6.0 25 0.075 3;
   18000 0.5 0.05 4.0 15 0.075 3;
   18000 1.5 0.20 6.0 25 0.025 1;
   18000 2.5 0.35 2.0 5  0.050 2;
   24000 0.5 0.20 2.0 25 0.050 3;
   24000 1.5 0.35 4.0 5  0.075 1;
   24000 2.5 0.05 6.0 15 0.025 2;
   30000 0.5 0.35 6.0 15 0.050 1;
   30000 1.5 0.05 2.0 25 0.075 2;
   30000 2.5 0.20 4.0 5  0.025 3;
   36000 0.5 0.20 6.0 5  0.075 2;
   36000 1.5 0.35 2.0 15 0.025 3;
   36000 2.5 0.05 4.0 25 0.050 1;
   42000 0.5 0.35 4.0 25 0.025 2;
   42000 1.5 0.05 6.0 5  0.050 3;
   42000 2.5 0.2  2.0 15 0.075 1;
]';

t=[344.14;325.08;421.69;409.99;419.84;416.03;
551.10;439.03;484.33;465.84;585.64;582.40;
534.64;599.60;503.80;595.60;566.70;516.20]';


for i=1:7 
p1(i,:)=(p(i,:)-min(p(i,:)))/(max(p(i,:))-min(p(i,:))); 
end 
t1(1,:)=(t(1,:)-min(t(1,:)))/(max(t(1,:))-min(t(1,:))); 

net=newff(minmax(p1),[4,1],{'tansig','logsig'},'trainlm');  
net.trainParam.epochs=2000;  
net.trainParam.goal=1e-10;  
net=init(net);
LP.lr=0.1;
net=train(net,p1,t1);
TT=sim(net,p1,[],[]);