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];
7 k8 Q1 U# e- v# u6 M4 iT=[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];
. Y$ W2 \6 ^  A$ C%  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
+ a3 w) j& D1 J5 N* f5 SinputWeights=net_1.IW{1,1}
9 N5 W- u% G1 _# _, {( vinputbias=net_1.b{1}
8 @: F1 G+ B* }5 ]; k' ^2 `%  当前网络层权值和阈值
1 {! R; P. F& a9 alayerWeights=net_1.LW{2,1}
layerbias=net_1.b{2}
& G# w$ C; i* U6 k, S) \$ E%  设置训练参数
, ^; `' L# m* _# F1 Inet_1.trainParam.show = 50;
net_1.trainParam.lr = 0.05;
net_1.trainParam.mc = 0.9;
3 U1 O1 W7 ]) b1 snet_1.trainParam.epochs = 10000;
0 i0 o' Y+ N0 t  y  K2 t2 Pnet_1.trainParam.goal = 1e-3;
# i6 v$ A' W+ t%  调用 TRAINGDM 算法训练 BP 网络
3 s- B* K; q6 D( w& G% D- _  o; |[net_1,tr]=train(net_1,P,T);
%  对 BP 网络进行仿真
A = sim(net_1,P);
  k* G2 e3 I1 T: @* u( [% |# k%  计算仿真误差
$ k& L8 f( U3 h# oE = T - A;
) \; s9 r; E4 ^+ R+ EMSE=mse(E)
, Q! T6 T0 E9 O: Q( W" n) 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)
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 。
$ P, X3 L  _) M! e6 X, N

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!!!!!!!!!!!