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]
[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t);          %原始数据归一化
1 W3 m+ B* b, K( }9 e9 z
net=newff(minmax(pn),[9,1],{'tansig','purelin'},'traingdx'); %设置网络,建立相应的BP网络
9 [, Y/ b: a/ K! B; n; Pnet.trainParam.show=2000; % 训练网络
* `8 W7 b$ Y7 W- J& f4 `$ X. D3 Tnet.trainParam.lr=0.01;
net.trainParam.epochs=10000;
& N0 R! @7 Y0 k% |) N7 K' a3 Y+ Hnet.trainParam.goal=1e-5;
3 v# x5 j" u  \. |# w# G' ?! S[net,tr]=train(net ,pn,tn);                              %调用TRAINGDM算法训练BP网络
3 \! z  ]' F+ X. h& |/ k9 C
0 y. ^/ y; }0 G. D0 ^7 ~an=sim(net,pn);                               %对BP网络进行仿真
: o- z+ B( Z6 W, Ja=postmnmx(an,mint,maxt);                     %还原数据
) ~4 o$ _+ T' `+ Q+ H( w, O6 w, `x=2001:2010;
newk=a(1,;
plot(x,newk,'r-o',x,t,'b--+')
legend('网络输出值/万人','实际人口数/万人');
" B) \' p5 Q- i" ~+ @8 L$ D9 O; ?3 N4 txlabel('年份');
( W6 R* t5 W/ ]7 r7 lylabel('人口数');
title('预测人口数对比表');

pnew1=[1079.38044723977,1125.65457635540,1173.91252408743,1224.23933874207,1276.72371473226,1331.45814888992,1388.53910347951,1448.06717620014,1510.14727747579,1574.88881534617]
pnew=pnew1
$ Z6 I5 t+ W+ zpnewn=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'


9 A7 H5 M5 N4 z! m* E预测的结果怎么都一样呀？》？？求助

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