求帮忙

lyfsgdhr

P=[0.1093,0.1110,0.1127,0.1141,0.1154,0.1164,0.1171,0.1175,0.1178,0.1179,0.1179,0.1179,0.1179,0.1180,0.1182];
T=[0.1110,0.1127,0.1141,0.1154,0.1164,0.1171,0.1175,0.1178,0.1179,0.1179,0.1179,0.1179,0.1180,0.1182,0.1185];
: @( P& O2 i9 P( B5 Z1 n%  创建一个新的前向神经网络
net_1=newff(minmax(P),[10,1],{'tansig','purelin'},'traingdm')
%  当前输入层权值和阈值
+ f2 A2 l9 I% T/ _inputWeights=net_1.IW{1,1}
, C7 ]# ~( H) |3 x# \  Uinputbias=net_1.b{1}
- |5 d6 V8 Q% M. y+ d%  当前网络层权值和阈值
layerWeights=net_1.LW{2,1}
layerbias=net_1.b{2}
& T! @0 o# q4 j9 l%  设置训练参数
net_1.trainParam.show = 50;
: d  d* l! v# C# p& Unet_1.trainParam.lr = 0.05;
1 v- p0 o+ ?6 Znet_1.trainParam.mc = 0.9;
$ J: c0 U6 |5 C& v8 M! enet_1.trainParam.epochs = 10000;
- y8 {' v2 W6 U; Z4 g8 knet_1.trainParam.goal = 1e-3;
%  调用 TRAINGDM 算法训练 BP 网络
[net_1,tr]=train(net_1,P,T);
! \6 ?+ w# v0 J6 G7 W! ?- D%  对 BP 网络进行仿真
! n6 a% |; P& y" @$ U6 X2 t' D- MA = sim(net_1,P);
%  计算仿真误差
E = T - A;
9 d0 }' e; s. B( H9 v+ {MSE=mse(E)
9 J' `' N# w, e7 i" I, yx=[0.1110,0.1127,0.1141,0.1154,0.1164,0.1171,0.1175,0.1178,0.1179,0.1179,0.1179,0.1179,0.1180,0.1182,0.1185]';%测试
sim(net_1,x)
4 Y, T! ]1 Z2 E; J7 R# X% {1 U这段程序是根据14年的数据，来预测下一年的，怎么算不出来啊 。
6 s5 j0 u. i) Y& M+ w

fffffffddf

这个太难了，我也不会

346010696

眼早就花了~~~

renzhe1

强烈支持。楼主万岁

rchjia

哦～～

tzw

楼主的帖子实在是写得太好了。可是我立刻想到，这么好的帖子，倘若别人看不到，那么不是浪费楼主的心血吗？经过痛苦的思想斗争，我终于下定决心，牺牲小我，奉献大我。我要拿出这帖子奉献给世人赏阅，我要把这个帖子一直往上顶，往上顶！顶到所有人都看到为止！  

xuwei198215

哦～～

heyingfeifei

楼主的帖子实在是写得太好了。可是我立刻想到，这么好的帖子，倘若别人看不到，那么不是浪费楼主的心血吗？经过痛苦的思想斗争，我终于下定决心，牺牲小我，奉献大我。我要拿出这帖子奉献给世人赏阅，我要把这个帖子一直往上顶，往上顶！顶到所有人都看到为止！  

yaotl17

留个脚印```````

lihao54

来报道!!!!!!!!!!!