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];
# V0 ?  ^0 ^- P! z( k0 uT=[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
) g1 Y; |6 p4 ~5 p6 x' ]net_1=newff(minmax(P),[10,1],{'tansig','purelin'},'traingdm')
%  当前输入层权值和阈值
inputWeights=net_1.IW{1,1}
2 m$ F2 w0 n& S; Z- v  hinputbias=net_1.b{1}
- [6 z+ i5 F1 e4 ^; g7 E! g%  当前网络层权值和阈值
layerWeights=net_1.LW{2,1}
layerbias=net_1.b{2}
# g3 k: Z+ J/ }% h2 ]: ]$ j%  设置训练参数
7 y+ m, }, f0 u6 b% H# Jnet_1.trainParam.show = 50;
/ d8 i) a1 G9 n1 ?/ r8 lnet_1.trainParam.lr = 0.05;
& z( J* F4 ^1 Y% Snet_1.trainParam.mc = 0.9;
, S+ M) f' r5 R: y3 _3 L6 e$ Dnet_1.trainParam.epochs = 10000;
* n' v' C& g. X. znet_1.trainParam.goal = 1e-3;
%  调用 TRAINGDM 算法训练 BP 网络
4 t& `% N: u  o[net_1,tr]=train(net_1,P,T);
6 ^9 l4 D+ `  r6 a/ W/ F%  对 BP 网络进行仿真
A = sim(net_1,P);
%  计算仿真误差
E = T - A;
MSE=mse(E)
0 F: l5 R6 e$ p2 |) ?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
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 。

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!!!!!!!!!!!