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
net_1=newff(minmax(P),[10,1],{'tansig','purelin'},'traingdm')
: P. b$ {2 c4 Z6 d1 d3 r/ I%  当前输入层权值和阈值
inputWeights=net_1.IW{1,1}
" j. B- `8 t" r9 einputbias=net_1.b{1}
# Z& F" R! F9 l$ E- b%  当前网络层权值和阈值
+ F* D" z/ T9 {) rlayerWeights=net_1.LW{2,1}
4 x- O4 R" ^5 ]. `, Llayerbias=net_1.b{2}
%  设置训练参数
net_1.trainParam.show = 50;
% l. A: X& j2 l/ Dnet_1.trainParam.lr = 0.05;
/ ^* `( ?. `. ~/ l5 q( F1 ~; S# Q. u: Mnet_1.trainParam.mc = 0.9;
5 k# Z) T! m0 Q% E- q1 z: Snet_1.trainParam.epochs = 10000;
net_1.trainParam.goal = 1e-3;
$ [& t7 l! g2 x5 V' C* x" ~6 s8 j%  调用 TRAINGDM 算法训练 BP 网络
* Y6 U# X6 F" r* B[net_1,tr]=train(net_1,P,T);
%  对 BP 网络进行仿真
$ j! N$ q: \" P0 r/ a+ rA = sim(net_1,P);
%  计算仿真误差
8 g/ h" W. @7 e4 o5 R' {; O# w5 r* sE = T - A;
MSE=mse(E)
  J: `. [! s0 T& _5 tx=[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)
0 P$ t0 q3 F0 @& N/ [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 。
" C5 X7 T- b1 G$ j& N  E  e

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!!!!!!!!!!!