Matlab BP神经网络股票预测实例与仿真分析

clc 
clear all 
close all 
aa=xlsread('sy1.xls'); 
at=[{'日期:2005-6-30至2006-12-1'},{'开盘价'},{'成交量'},{'最高价'},{'最低价'},{'收盘价'}]; 
ys='brgmcyk'; 
 
pd=aa(1:330,:)'; 
[pn,minp,maxp]=premnmx(pd); 
pr=[pn(:,1:320);pn(:,2:321);pn(:,3:322);pn(:,4:323);pn(:,5:324)]; 
% px=[pn(:,1:300);pn(:,2:301);pn(:,3:302);pn(:,4:303);pn(:,5:304)]; 
px=pr(:,1:300); 
py=pn(5,6:305); 
 
pX=pr(:,301:320) 
pY=pd(5,306:325); %pn(5,306:325);   
 
net1=newff(minmax(px),[16,1],{'tansig','purelin'},'trainlm'); %{'tansig','logsig'},'traingdx'); {'logsig','purelin'} 
net1.trainParam.show=1; 
net1.trainParam.epochs=2000; 
net1.trainParam.goal=0.001; 
net1.trainParam.max_fail=5; 
net1=init(net1); 
[net1,tr,Y,E]=train(net1,px,py); 
 
s=sim(net1,px); 
 
er=py-s; 
 
figure