求

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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];
3 z2 u$ N7 Y( {: I/ t/ t3 Q, z( h( m* _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')
%  当前输入层权值和阈值
7 E# q7 Y, W( {6 ~/ IinputWeights=net_1.IW{1,1}
. J1 [" G( s$ Tinputbias=net_1.b{1}
; s  z2 O& E6 ?% W2 _9 c8 L1 w%  当前网络层权值和阈值
$ a3 s" o1 d7 L. elayerWeights=net_1.LW{2,1}
layerbias=net_1.b{2}
8 h, {0 i, B+ p) f9 ^: q& U4 t! F%  设置训练参数
8 Y0 t0 ]3 r$ H3 n" Q1 S6 ^net_1.trainParam.show = 50;
net_1.trainParam.lr = 0.05;
' l, o( |6 C1 e3 |net_1.trainParam.mc = 0.9;
+ Y9 ^4 X- i% s- anet_1.trainParam.epochs = 10000;
net_1.trainParam.goal = 1e-3;
%  调用 TRAINGDM 算法训练 BP 网络
[net_1,tr]=train(net_1,P,T);
6 {5 l# w! P( _7 P%  对 BP 网络进行仿真
- e4 z/ A/ e3 m& X) vA = sim(net_1,P);
' a3 w; e$ w0 |%  计算仿真误差
E = T - A;
, _; m# G! U6 T/ W. @7 hMSE=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)
- X7 l, w( i9 {8 M. ^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·····

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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。