jjjj.txt

vc编程实现bp神经网络

## 样本的输入层的数目: ##
8
## 样本的隐含层的数目: ##
12
## 样本的输出层的数目: ##
1
## 训练网络所采用的神经网络算法: ##
1
## 网络中使用的函数的索引值: ##
0
## 输入层到隐含层的权值矩阵 ##
-1.0060464597781213  0.0507494780584586  0.0777917890538012  1.2661589255688188  0.1598924187399066  -0.0478960290916425  0.3917662145428607  0.4954088390990136  
0.5847506505775595  0.4922557828690102  -0.8810125143590177  0.6677754206879802  0.4149968588590404  0.0269745330279517  -0.6212389616993290  -0.8684195867475263  
-0.5531615113603448  0.1343271153432945  -1.1701382492968533  0.4099650403470573  1.4872837726423380  -0.0680730717232164  -1.2265974918274474  -0.0061591198858230  
-0.9503532028198741  -0.2831403084941463  0.7563627965604930  0.6508179293711529  0.2163786918691369  0.2104414243341548  0.0255055316293126  0.1233633867249749  
-0.0913004212219376  -0.3058469179450838  -0.5544628654979377  0.4106661923871046  0.5763740395222252  0.6042033571571849  0.3712245639280027  -0.4300137732655112  
0.7351819027579380  0.4361247928777495  0.8820192299531413  0.8262892950655542  0.0591135266851064  -0.7170461101467160  -0.1056207737090805  -0.5713600052617663  
0.7552806406090814  -0.5782786730318137  0.4396557412788639  0.6919967950086828  0.9965584296764544  0.9996415378910757  0.1033417668533761  -0.3048787714114519  
-0.3528941335852270  -0.1931232632645653  -0.0820947205295943  -1.5628376430084630  -0.0997464705001001  -0.7935211339682936  -0.4079713647142908  -0.2120125128670369  
-0.9472436697675920  0.7924497406105505  0.1861472831691655  -0.2236176060414883  0.1544341029194493  0.3778533300289480  1.3095946539995647  0.2496668361506036  
-0.0425112515270050  -0.6968642814154907  0.8513173742744752  0.0668551875485474  -0.1774492407185385  0.8875540882316346  0.8527212257103710  -1.2062515528829516  
0.2132609955683567  -0.0312721061744916  -0.4703666048036859  0.6107630087043142  0.3807451605708956  -0.2574959352489405  -1.6372723331279266  0.0799793672677743  
-0.2347255324741489  0.6170149829738619  -0.4973062554731395  0.8496217346407807  0.5010695623510122  -0.3077525255680907  -1.1935555306585586  0.4888299506675676  
## 隐含层的阀值矩阵 ##
-0.0162053285317545  
-0.8729209265419476  
0.3995178075502793  
0.0096133304849391  
-0.7050080874050111  
0.8991668446913053  
-0.7168492690816981  
0.8102359080782494  
0.3857844782860805  
-0.3939024018066958  
-0.1468855861079745  
-0.8592486342967010  
## 隐含层到输出层的权值矩阵 ##
1.3833980929993597  -0.5655872780632134  -4.1834549506141911  0.9152272274416820  0.1817574159761140  0.3898202192939654  0.7420441196722788  -3.0458399292006084  0.9256039548629443  2.0255795064425604  -2.8790837960378726  -1.0859808596882774  
## 输出层的阀值矩阵 ##
0.4640339365825373