求助

422258511

p=[724.570000000000,739.774223126620,771.489090673942,804.563606600594,839.056060404793,875.027240514377,912.540541418428,951.662075391767,992.460789009143,1035.00858465455]
t=[724.570000000000,746.620000000000,778.270000000000,800.800000000000,827.750000000000,871.100000000000,912.370000000000,954.280000000000,995.010000000000,1037.20000000000]
- y9 \2 T5 c4 i- S' z! ] [pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);          %原始数据归一化
3 R/ z" a+ Q" f7 d) ?: |
+ X+ \# X/ M9 u1 dnet=newff(minmax(pn),[9,1],{'tansig','purelin'},'traingdx'); %设置网络,建立相应的BP网络
net.trainParam.show=2000; % 训练网络
net.trainParam.lr=0.01;
8 r+ C" X- [  i! Gnet.trainParam.epochs=10000;
: @8 b3 ^; s( D" |2 c9 @net.trainParam.goal=1e-5;
( M, x  E/ g& [[net,tr]=train(net ,pn,tn);                              %调用TRAINGDM算法训练BP网络
% V6 D  ?2 q# ^- W
& x# _6 F: o: m3 ]9 Y% f! Can=sim(net,pn);                               %对BP网络进行仿真
: H6 m, z% g5 q3 s% w2 M3 da=postmnmx(an,mint,maxt);                     %还原数据
x=2001:2010;
newk=a(1,;
2 o, p/ r7 F! F. P+ Lplot(x,newk,'r-o',x,t,'b--+')
& n4 ^2 r( S4 r# Plegend('网络输出值/万人','实际人口数/万人');
xlabel('年份');
+ O+ E( `3 r8 j  jylabel('人口数');
) i) O. c5 f& w" l0 q* @title('预测人口数对比表');

9 G: }3 v' c. o  e% `pnew1=[1079.38044723977,1125.65457635540,1173.91252408743,1224.23933874207,1276.72371473226,1331.45814888992,1388.53910347951,1448.06717620014,1510.14727747579,1574.88881534617]
* a; I6 j- t( G" ?5 j7 Upnew=pnew1
9 |3 }, @  C3 ^  @pnewn=tramnmx(pnew,minp,maxp);
anewn=sim(net,pnewn);                               %对BP网络进行仿真
anew=postmnmx(anewn,mint,maxt);                     %还原数据
y=anew'


+ j2 ]- z4 {% C; O' ^- c1 K2 W预测的结果怎么都一样呀？》？？求助

wssl103050