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
1 G) L" S5 f# H+ @' `: ~) Hnet_1=newff(minmax(P),[10,1],{'tansig','purelin'},'traingdm')
2 j$ X- n* F' \! E8 J4 z%  当前输入层权值和阈值
0 B: H! z" ?$ ~1 ^* ^! u  z2 dinputWeights=net_1.IW{1,1}
" L- L# l: h7 Z! B3 P3 [7 oinputbias=net_1.b{1}
%  当前网络层权值和阈值
$ u1 U% y6 {( k5 h, OlayerWeights=net_1.LW{2,1}
layerbias=net_1.b{2}
% |9 f( d3 f" X/ {%  设置训练参数
* A0 m1 k0 s4 P  M8 l+ P' Z; Rnet_1.trainParam.show = 50;
net_1.trainParam.lr = 0.05;
+ v! X% _0 P, o: V1 B8 Onet_1.trainParam.mc = 0.9;
net_1.trainParam.epochs = 10000;
+ @& E, K/ j+ y) onet_1.trainParam.goal = 1e-3;
%  调用 TRAINGDM 算法训练 BP 网络
[net_1,tr]=train(net_1,P,T);
& S3 P; }7 |- Z$ Y%  对 BP 网络进行仿真
  N# ?5 Z7 r6 r/ H! ~7 xA = sim(net_1,P);
%  计算仿真误差
4 p3 J. X1 ^( aE = T - A;
% X: f1 x; K+ zMSE=mse(E)
( [* d; s: {# S7 Y' ^& nx=[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 。
4 {0 N& X/ A/ V  g6 j

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!!!!!!!!!!!