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];
%  创建一个新的前向神经网络
! d* v& K! P4 _% q2 p% unet_1=newff(minmax(P),[10,1],{'tansig','purelin'},'traingdm')
+ {& o/ C4 c% O- W$ s%  当前输入层权值和阈值
; p6 W2 [9 X' ?2 w( r0 JinputWeights=net_1.IW{1,1}
inputbias=net_1.b{1}
1 t8 g" v1 h3 O8 A( v%  当前网络层权值和阈值
layerWeights=net_1.LW{2,1}
. `* }6 k  i  Y# j! {! @layerbias=net_1.b{2}
%  设置训练参数
net_1.trainParam.show = 50;
# m' J- v, p$ [3 K- U& v' pnet_1.trainParam.lr = 0.05;
$ w! _, y, _: o/ [) |6 }5 I" U: k& rnet_1.trainParam.mc = 0.9;
6 [, O6 ~: `1 E3 f7 m# [8 d, Qnet_1.trainParam.epochs = 10000;
net_1.trainParam.goal = 1e-3;
6 C; j: A: |5 v) F# i& }%  调用 TRAINGDM 算法训练 BP 网络
5 C" d1 C' T6 ]. }8 y8 z5 \: D[net_1,tr]=train(net_1,P,T);
0 p4 O1 j1 A& b# u" t%  对 BP 网络进行仿真
* Q4 Z( b3 H1 u) H+ a" K  c9 kA = sim(net_1,P);
%  计算仿真误差
E = T - A;
MSE=mse(E)
x=[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
5 L% r4 p" s. u; D* |" Nsim(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 。
  q5 R" v, R# F7 o% B0 o. ?* |- P/ R

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!!!!!!!!!!!