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];
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];
" o2 M; V% O% U7 Y6 V& V%  创建一个新的前向神经网络
net_1=newff(minmax(P),[10,1],{'tansig','purelin'},'traingdm')
* c6 Z; m/ I# }4 f%  当前输入层权值和阈值
% n* g9 P& g7 I. |; q% YinputWeights=net_1.IW{1,1}
inputbias=net_1.b{1}
! ^, Y8 F" h5 C# M2 ]%  当前网络层权值和阈值
; p/ |% E" t( I7 qlayerWeights=net_1.LW{2,1}
0 v; [. V1 d; P4 y8 G% |layerbias=net_1.b{2}
- t* V) A! L2 {; m1 ]$ k%  设置训练参数
: }' W: c# U% m" i0 wnet_1.trainParam.show = 50;
net_1.trainParam.lr = 0.05;
net_1.trainParam.mc = 0.9;
1 b6 q4 Q, k( b% inet_1.trainParam.epochs = 10000;
net_1.trainParam.goal = 1e-3;
7 X1 b1 h( K! l. S. t' p4 ]%  调用 TRAINGDM 算法训练 BP 网络
) m$ t( K' R8 O- G% F: H& ][net_1,tr]=train(net_1,P,T);
%  对 BP 网络进行仿真
8 T2 J+ ]9 [% l( C. A7 tA = sim(net_1,P);
%  计算仿真误差
E = T - A;
MSE=mse(E)
' P0 A# E  j: Y0 n: ax=[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 。
8 A& S1 Y6 t! X* R- X

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。