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];
! g, |: _3 k8 ~" Y7 Q1 a%  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
; ^5 v8 \+ d* l: _& p* a9 einputWeights=net_1.IW{1,1}
inputbias=net_1.b{1}
- Z6 m% |9 v7 Z3 k1 X" q%  当前网络层权值和阈值
$ _! L: R, C) R  zlayerWeights=net_1.LW{2,1}
/ m2 m7 r& C( u. g! Z2 c3 t! R( [layerbias=net_1.b{2}
1 R* z# U5 c. J' C) `, j+ n( X% g& G%  设置训练参数
7 M/ F9 w/ r, U! p/ r, r# jnet_1.trainParam.show = 50;
net_1.trainParam.lr = 0.05;
/ D- I1 L5 Q% c  j$ tnet_1.trainParam.mc = 0.9;
net_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);
% w5 K0 X1 H- p& O/ z- s%  对 BP 网络进行仿真
A = sim(net_1,P);
0 J2 v. E9 |# T, t9 ~) _( y%  计算仿真误差
( ?% F9 A( ]( i0 ~5 R/ hE = T - A;
4 Z/ u6 C" y3 t9 yMSE=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 。
8 T/ t+ i/ _- m# ^

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。