function?PF=myNNet（InPeriod）?
%程序說明：Period為預(yù)測期數(shù)；PF為所有變量預(yù)測值的矩陣；MSE為樣本的均方誤差；

%%載入文件
%?In=load（‘GDP.txt‘）;

%%%數(shù)據(jù)歸一化處理
In=In‘;
[ab]=size（In）;
P=In（1:a-1:）‘;
T=In（2:a:）‘;
[PnPminPmaxTnTminTmax]=premnmx（PT）;%歸一化－1～1之間

%%創(chuàng)建一個(gè)隱藏層含三個(gè)神經(jīng)元的三層神經(jīng)網(wǎng)絡(luò)
net=newff（minmax（Pn）[4b]{‘tansig‘‘purelin‘}‘traingdm‘）;

%?%%設(shè)置輸入層參數(shù)
%?inputWeights=net.IW{11};
%?inputbias=net.b{1};
%?%%設(shè)置隱藏層參數(shù)
%?layerWeights=net.LW{11};
%?layerbias=net.b{2};
%?%%設(shè)置訓(xùn)練參數(shù)
net.trainParam.show=100;
net.trainParam.lr=0.5;
net.trainParam.epochs=10000;
net.trainParam.mc=0.9;
net.trainParam.goal=1e-3;

%%訓(xùn)練網(wǎng)絡(luò)
net=train（netPnTn）;
%%仿真
A=sim（netPn）;
%%計(jì)算殘差
E=Tn-A;
ms=mse（E）;

%%預(yù)測Period期
P1=In（a:）‘;
k=Period;
for?i=1:k
????P1=tramnmx（P1PminPmax）;%預(yù)測數(shù)據(jù)歸一化
????T1=sim（netP1）;
????T1=postmnmx（T1TminTmax）;%反歸一化
????if?i==1
????????PF=T1;
????else
????????PF=[PFT1];
????end
????[cd]=size（PF）;
????P1=PF（:d）;
end
PF=PF‘;
save?‘result.txt‘?PF?-ascii?;

?屬性????????????大小?????日期????時(shí)間???名稱
-----------?---------??----------?-----??----

?????文件???????1847??2010-01-08?21:10??QG.txt

?????文件???????1097??2010-01-08?22:06??myNNet.m

?????文件???????1661??2010-01-13?15:16??NNetFF.m

?????文件???????1374??2010-01-13?15:21??NNetGRNN.m

?????文件???????1428??2010-01-13?15:21??NNetRBF.m

?????文件????????267??2010-01-07?10:54??testmain.java

-----------?---------??----------?-----??----

?????????????????7674????????????????????6