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];
; I4 c5 [$ E3 m4 @4 s! tT=[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
inputWeights=net_1.IW{1,1}
inputbias=net_1.b{1}
%  当前网络层权值和阈值
layerWeights=net_1.LW{2,1}
! ^" ~+ e1 F, h* `layerbias=net_1.b{2}
' m# E4 q" [/ ^, h+ x% z6 X  x%  设置训练参数
7 G; x8 @5 G8 o* ?& mnet_1.trainParam.show = 50;
net_1.trainParam.lr = 0.05;
: O% M* U% J* {1 ~5 a8 Rnet_1.trainParam.mc = 0.9;
net_1.trainParam.epochs = 10000;
2 y- R9 r3 \+ q8 A" C' _3 V$ mnet_1.trainParam.goal = 1e-3;
* w3 G7 L% [# g/ `2 i9 w1 m' f%  调用 TRAINGDM 算法训练 BP 网络
[net_1,tr]=train(net_1,P,T);
5 g4 l7 ~4 D9 g9 p0 i) U%  对 BP 网络进行仿真
A = sim(net_1,P);
%  计算仿真误差
8 g1 ~, e: f9 rE = T - A;
MSE=mse(E)
% A' T+ u3 d; {/ u$ e3 J4 p7 Q& r- p! Tx=[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
7 n! w: c& A+ [) b# |9 msim(net_1,x)
0 T$ ?% I; P# }3 Z7 [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。