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];
) @8 m  U+ ]9 D%  创建一个新的前向神经网络
0 b' b( D2 C4 _; E( h+ {: E* Dnet_1=newff(minmax(P),[10,1],{'tansig','purelin'},'traingdm')
9 }0 l# W: g7 R%  当前输入层权值和阈值
6 U" r$ Q1 L/ k1 i5 |8 r, qinputWeights=net_1.IW{1,1}
inputbias=net_1.b{1}
%  当前网络层权值和阈值
2 Y2 |: ]+ P0 r; Z% m/ WlayerWeights=net_1.LW{2,1}
7 E, V7 p8 b* U( _) n4 g+ }8 Qlayerbias=net_1.b{2}
2 Z0 L2 x) C- I- o* ^: k& V%  设置训练参数
8 d1 p" O; a: t6 K! Hnet_1.trainParam.show = 50;
net_1.trainParam.lr = 0.05;
net_1.trainParam.mc = 0.9;
4 q, `  @! h) _/ G& q3 Q9 l4 H; \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);
% a$ q( f/ t) e%  对 BP 网络进行仿真
: [1 o; u; h8 D9 m# z: z8 JA = sim(net_1,P);
9 o" U+ o/ x7 e7 {%  计算仿真误差
" R: D8 x# o# q- V, {7 w& t& ~( j. C' QE = T - A;
MSE=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)
7 |7 J! `# n% }0 [0 T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 。
$ y" L% C. @3 E( 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。