求

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];
; x% l  A! T( K# U6 g0 [4 N$ KT=[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')
%  当前输入层权值和阈值
inputWeights=net_1.IW{1,1}
inputbias=net_1.b{1}
%  当前网络层权值和阈值
layerWeights=net_1.LW{2,1}
5 f1 z1 j# U4 @  C8 I" I9 \- Blayerbias=net_1.b{2}
) W: |! e8 u, Y# Z  h- c%  设置训练参数
7 b6 n8 s& J3 g7 P0 R9 L1 z4 wnet_1.trainParam.show = 50;
net_1.trainParam.lr = 0.05;
net_1.trainParam.mc = 0.9;
( Z( z1 t. J& n2 \# Gnet_1.trainParam.epochs = 10000;
- y& S+ _* l, @' S1 r7 H* `" lnet_1.trainParam.goal = 1e-3;
%  调用 TRAINGDM 算法训练 BP 网络
[net_1,tr]=train(net_1,P,T);
1 m( h& W$ k0 ]/ F, F1 u%  对 BP 网络进行仿真
A = sim(net_1,P);
, Z  `* S4 n9 Z$ q3 o& Q2 f% C" C%  计算仿真误差
E = T - A;
: Q+ e) q' \) M5 I# m; q$ m$ NMSE=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
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 。

小青菜

看上去好烦哦

zhou2yong888

看不懂·····

fffffffddf

...........................................

kxhu

哦～～

hbchina99

鉴定完毕！  

ask4kevin

看起来好~~像啊~~~~~

talent212121

鉴定完毕！  

hyxie616

楼主，你写得实在是太好了。我惟一能做的，就只有把这个帖子顶上去这件事了

pankg

我基本上是采用看英语文章的办法，先泛读，再精读，再一句一句看，最后再提纲挈领，总算是明白一点了，当然，也可能还是领悟错了。最后要说的一句话是：楼主，你很牛叉，希望你不是真的有病。