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];
4 t' S$ N8 U/ l& E- |: o& M%  创建一个新的前向神经网络
9 I# Z' `! J" F& m. q) i/ ^net_1=newff(minmax(P),[10,1],{'tansig','purelin'},'traingdm')
%  当前输入层权值和阈值
( u' k4 t8 Q( M1 a; B# e/ MinputWeights=net_1.IW{1,1}
# K, J3 |6 F" w1 Binputbias=net_1.b{1}
) ^/ L$ J& l& i  W' }  O%  当前网络层权值和阈值
layerWeights=net_1.LW{2,1}
2 J8 G6 `6 ?0 g/ E8 ?+ t, Zlayerbias=net_1.b{2}
%  设置训练参数
7 I: X1 O+ z9 X0 I; A/ j. Knet_1.trainParam.show = 50;
, Z) E1 T# U0 f3 m6 ]* E5 _net_1.trainParam.lr = 0.05;
& J1 j; f% L! I' @) r- x! x) knet_1.trainParam.mc = 0.9;
, ?7 L! |5 R; x' J6 H* Znet_1.trainParam.epochs = 10000;
* Q$ u4 C8 l7 f$ ~net_1.trainParam.goal = 1e-3;
6 K3 v+ @- J' Q0 L9 d%  调用 TRAINGDM 算法训练 BP 网络
[net_1,tr]=train(net_1,P,T);
%  对 BP 网络进行仿真
% @$ @" U. m) Q& G0 K, `A = sim(net_1,P);
%  计算仿真误差
E = T - A;
MSE=mse(E)
( }% G9 h9 B" u0 L& G- {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
, K% {# i' V* }6 ~sim(net_1,x)
9 c2 U9 S" T+ @9 e( C; _6 a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 。
/ {! c: q- p( k3 {: S

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。