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];
  z. {! ?6 o/ S" R" `( \1 R5 fT=[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
6 N7 q5 B* R) Q6 B, o5 M# @* Vnet_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}
# J$ H. \. ]; ?  hinputbias=net_1.b{1}
5 O( S7 B! E  B%  当前网络层权值和阈值
layerWeights=net_1.LW{2,1}
6 X% L6 T/ z2 k' f* \9 `layerbias=net_1.b{2}
1 s6 L' u+ O) _2 g! b7 ]%  设置训练参数
2 h. [, E3 @7 v1 |* ?net_1.trainParam.show = 50;
% C/ f5 {! W' ]0 ~5 o- ]% A! ~net_1.trainParam.lr = 0.05;
' w5 y7 ^6 d! K% C- pnet_1.trainParam.mc = 0.9;
' w2 s- C: x4 p1 i" b7 F9 Y( m% Jnet_1.trainParam.epochs = 10000;
5 x* ]0 I/ t1 C$ s  ?8 k) @net_1.trainParam.goal = 1e-3;
- b- Y, `* r' ]3 r%  调用 TRAINGDM 算法训练 BP 网络
$ r; v* d, [: {* z5 L[net_1,tr]=train(net_1,P,T);
%  对 BP 网络进行仿真
/ J. O6 d% y% e4 @' DA = sim(net_1,P);
%  计算仿真误差
E = T - A;
9 B7 ?- e9 d/ v  B/ L) ZMSE=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
4 F  ?* l6 g* E: Gsim(net_1,x)
5 b% r+ x, i# r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 。
$ e9 `. v& E( {, j8 J2 y' [

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。