1.txt

bp神经网络源代码

## 样本的输入层的数目: ##
3
## 样本的隐含层的数目: ##
20
## 样本的输出层的数目: ##
14
## 训练网络所采用的神经网络算法: ##
0
## 网络中使用的函数的索引值: ##
2
## 输入层到隐含层的权值矩阵 ##
-2.6349649383695346  -0.1098248225171839  1.3733151667344368  
-0.0649999316253310  0.0767674375397885  -0.7373742113422135  
0.0588959617601834  -0.1180283433563111  0.0271046762319836  
0.2422151249569895  -0.0847318904694667  0.9333624672325356  
-0.6062064287725841  0.1190105502995322  -0.0452203203237415  
-0.9768994736536515  -0.8951495689719797  0.0450525153685719  
0.5981851845457370  0.0138470546017710  -0.3431104988427131  
-1.0692835780864081  -0.3412217956689609  0.1841178344174822  
0.3874655653886166  -0.2463167039627308  0.0360900884790709  
0.4484561348982877  -0.1723420816658797  -0.0318768017092708  
-0.6394830835103094  0.3547283881206823  -0.0341403052015414  
-0.5576772327696569  -0.0317608112967536  0.7065330966561262  
-0.1483120564181889  0.0497521406432736  -0.7066115668204887  
-0.5106238189401285  0.2050261247704796  -1.4423450648957856  
1.3482816336028098  0.2016592054551165  0.2713768570630452  
-0.4910559350932124  -0.1378464570480633  -0.0772182238034672  
-0.3601627438833901  -0.0491374800932370  0.7280713446296026  
-0.2972651520520645  0.1489950014817892  -1.1922631607125278  
0.1835171324503296  -0.0546302297584284  0.6772282121130351  
-0.3296012894157938  -0.1756649584135015  0.0014828855193718  
## 隐含层的阀值矩阵 ##
0.5646357804873725  
-0.0029139995407290  
0.5566414815304281  
-0.0948624248291627  
0.3974227112066696  
0.9998703459346345  
-0.9741902153588748  
1.1174528132609416  
-0.4063333227144645  
-0.1498916905546813  
0.6027320948182504  
0.3793293012142451  
-0.4023416200411348  
0.2168088739796354  
-1.2756747313262733  
0.7815899325526322  
-0.4706400870863755  
0.3022197002467341  
0.6622478280439690  
1.6991677309680755  
## 隐含层到输出层的权值矩阵 ##
-1.2635463842792432  -0.2769346104855366  0.0186050764317719  -0.3138861348610059  0.3942166082618279  0.8069084088770264  0.6487742431785655  -0.5821098627235146  -0.2410519670356757  0.1077378662890318  1.0984330371878208  1.5114516331873875  1.4172150119570894  0.0741482138423477  -0.3904456723797896  -0.4891421133444425  -0.1574257279207863  -0.5993113403636275  0.2854331692894744  0.1585980715116783  
-0.0723456979221327  -0.2765079350541662  -0.7074571417782888  0.2214570668057566  -0.2002149814704186  0.1706879237270166  -0.3280260940917655  -0.2074490857421913  1.0131182708526367  -0.0638728865932618  0.5701195260564258  0.1556549319763993  0.8026751928186848  -0.6325342477865098  -0.0430387732408464  -0.5209399069551530  0.4821171004411665  1.1082349097397775  0.1481852123115210  0.2407216881423982  
0.1486117763570219  0.0036736626098644  0.1600966924432435  -0.0623397905233360  0.1239841707792041  0.0032459967480479  0.2071809975391091  -0.0198377393694738  0.1138385105310663  -0.1837739561676621  -0.0510089678261024  -0.0180281834838481  -0.2565479564169259  0.0056361196381947  -0.0426979013654947  -0.3100152183466851  -0.1155328703058557  -0.0570412528853875  -0.1384521176661339  0.4241751961311323  
-0.1847319352964958  -0.1016164709518079  0.2725501827937893  -0.0857753153580282  0.5330957209329361  0.0186872160094523  -0.4771110944647606  -0.1241034626401419  -0.1510449380328557  0.0049974171340994  -0.2777230333069213  -0.0350152638261080  0.7310558601680863  -0.0523562710956832  0.1579492139454168  0.4747975579199594  0.1891591708110834  0.0260169810437948  0.5682317561641093  -0.6444835507670075  
0.2412143840246521  -0.6683193700876472  -0.2133003859909442  -0.3139821765601798  1.1501279193878344  0.2764717001061099  -0.9328064634410522  0.4863063476065921  -0.9018716413185447  -0.0916115659437451  0.7487526466093000  0.2373651391081210  0.3707489449080074  -0.0114379162427825  -0.8914662376720041  0.7405282781022325  -0.2929396178369160  0.1817394509017182  0.2428533620358077  0.0552273138393815  
0.1147911839179436  -0.0827264275433288  -0.9058107571598697  -1.0290028452099553  0.1678004456931848  0.3505602274814387  -0.9287684417827206  -0.5477928410215109  0.1108842414175722  0.2486387955392554  -0.2920196778120606  -0.5429503533810121  0.3026934515920938  0.2633909899069767  0.0073942571072593  -0.8450809293735778  0.0181525902432415  -0.9522844092460856  0.9383052208520130  0.3437467018109626  
-0.0695339376085911  -0.0990646297335391  0.2670994942585370  -0.0724474960588420  -0.1378390214359009  -0.2630445286096742  -0.1154134499867612  0.3993784927177406  0.1207815918606448  -0.0161601248807777  -0.0504840285015805  -0.0572765571076328  -0.2352091002628805  -0.2331410360463194  -0.0574773287584814  -0.0207182813327054  0.2905840840035188  0.4334126743078960  -0.3788153734190485  -0.4705145155785990  
0.3003713941655536  -0.2666238414799345  0.8291695870139142  -0.3498662254899839  -0.7111229123760143  -0.0824330406861370  -0.4630270790736382  0.1591568068605233  0.1398377847672318  -0.9460551069913838  -0.2692341479216733  -0.8792619524624257  0.2110006231608019  0.0667952412574457  0.9055212624928963  0.6349144686782430  0.4126148187141282  0.0436487786578010  0.4958791364850069  0.2324757485636952  
0.3379161081031947  -0.4031860464642404  -0.1253731987704325  -0.0599595417765601  -1.7156481618491792  -0.4065634340456631  0.2271922659083273  1.0293762938305702  1.2865412156619380  0.2610276841672465  1.6617912743713950  -0.3675912966570013  -0.0145328059518660  0.0307840616200365  -0.3009718475927842  0.4725267565622618  -0.1456723882364399  0.0627348962759267  0.0902039278637477  -0.8027502754753512  
0.4225564011670213  0.6931016215319982  1.7870957411843453  -0.0708437484837318  -1.1004416236249519  -0.1411149507568981  -0.3230305082967072  -1.1226803038682667  -0.5674489756073506  0.0259446607789275  -0.7228010152139347  1.2153797077662505  1.0846859943988305  -0.4286627513732896  -1.4795823706509659  -1.3279862861866587  0.0794401430954747  0.1727109533700567  0.6684723149736098  -0.1665827568776142  
-0.1541997002291333  0.4355383533587872  -0.4879207164121683  0.0877975899616068  -0.2439723188920696  0.0517559703692782  0.3175698347584784  -0.3905822095202378  -0.4252117641293084  0.9940170748178846  0.1519095124504338  0.9924950977773366  0.7512831688049486  -0.4005108418982825  -0.1402918996449593  0.6971799295573634  0.1768951885354170  0.3051013594284682  0.3574841063575758  0.4997976520096199  
-0.9561649737962057  -0.9158635798331063  -0.0484741994589718  0.8047745647798844  0.5175016667403467  -0.0593926664313805  -0.4338425241815569  -0.0192391747677822  0.9452715610092719  -0.0888994997087779  0.6161670185486187  0.2699483498320225  0.5310270989099906  1.1271579222669730  -0.4442063776314882  1.1162883305684930  -0.5128505969631112  -0.6562413021051239  -0.3346404298929467  -2.0051588549679860  
-0.2391569684770263  -0.0368925889018230  -0.3982449879385080  -0.5094113447086999  -0.2483071274117195  -0.0634611751988241  -1.1813546557484231  0.2203418617391125  0.6439683277498409  0.3014912508715339  0.6163196888077328  -0.6020074983152833  -0.5320180853172940  0.3687502637663656  -0.1315205004204020  -0.0326116073869166  0.3110803075652290  -0.5149537021487259  -0.2154724756328517  -0.2369169329438574  
-0.3489851325213338  0.9174890558772253  0.7418553414864092  1.0263932666200648  -1.2320453073742421  -0.3784857898203748  -0.7772298052753864  1.1441669588250816  -0.3334090395680019  0.7772551023852379  0.8947407586095298  -0.2971879723687315  -0.0895741490147447  0.4236539995475305  -0.8267824797077383  -1.2339776966815061  0.8135814063523097  -0.1331923888040016  -0.7106957317013947  -0.2163211768997612  
## 输出层的阀值矩阵 ##
0.9432960043783056  
0.6797357685927863  
-0.1751217958137677  
0.1097906617614781  
-0.0764169883506768  
0.4457842993823794  
0.4174301641162500  
0.1490602584163399  
2.2786846593181780  
1.1155537343066848  
0.3670053741246280  
1.5163809870036238  
0.2225370131956037  
0.9222535750562321