Y是输出比如0.5081

X就是迭代次数

Y=（-k*ln（x*r2/r1））+b

K，b都是常数可以由已知数值代出来，r1=0.1 ，r2是学习率

While(Math.abs(h-s))<0.0001---s1

While(Math.abs(h-s))<0.00001---s2

While(Math.abs(h-s))<0.000001---s3

Y=（-k*ln（x*r2/r1））+b------1

Yt=[n+(n-m) *(2*log(s1/s2)-1)/2] *k+b---------2

*** ***

y=a.ln(n)

*** ***

（为了加快速度这个程序与《学习率对神经网络的影响-乙烷，乙烯，乙炔的分子模型试验数据对比》中的程序有区别，特征值不一样，但只影响k和b的值，趋势是一样的）

输出     迭代次数
1 0.519145 95384 1 -11.4657
1 0.517366 95519 2 -11.4671
1 0.521007 96570 3 -11.478
1 0.515995 97237 4 -11.4849
1 0.51779 97860 5 -11.4913
1 0.515367 98687 6 -11.4997
1 0.518125 101388 7 -11.5267
1 0.51642 101713 8 -11.5299
1 0.518258 101792 9 -11.5307
1 0.520261 102643 10 -11.539
1 0.518114 102968 11 -11.5422
1 0.516798 102969 12 -11.5422
1 0.518629 103839 13 -11.5506
1 0.51629 104245 14 -11.5545
1 0.520042 104468 15 -11.5566
1 0.517567 104778 16 -11.5596
1 0.515846 104799 17 -11.5598
1 0.515865 105221 18 -11.5638
1 0.516792 106761 19 -11.5783
1 0.515333 106895 20 -11.5796
1 0.515982 107135 21 -11.5818
1 0.517728 107504 22 -11.5853
1 0.51667 108496 23 -11.5945
1 0.516331 109355 24 -11.6024
1 0.518111 109615 25 -11.6047
1 0.511998 109718 26 -11.6057
1 0.514129 109733 27 -11.6058
1 0.521731 109916 28 -11.6075
1 0.516926 110223 29 -11.6103
1 0.5175 112450 30 -11.6303
1 0.517877 112839 31 -11.6337
1 0.519691 113231 32 -11.6372
1 0.515625 113565 33 -11.6401
1 0.515639 113917 34 -11.6432
1 0.513849 115053 35 -11.6531
1 0.517363 115481 36 -11.6569
1 0.518278 116278 37 -11.6637
1 0.517469 116522 38 -11.6658
1 0.518217 116953 39 -11.6695
1 0.51451 117781 40 -11.6766
1 0.51699 121418 41 -11.707
1 0.516391 123261 42 -11.7221
1 0.517829 126865 43 -11.7509
1 0.518721 130235 44 -11.7771
1 0.513979 149211 45 -11.9131
1 0.512571 186448 46 -12.1359
1 0.51454 196496 47 -12.1884
1 0.514146 209615 48 -12.253
1 0.51422 223214 49 -12.3159
1 0.512343 263827 50 -12.483
2 0.509299 385070 1 -12.8612
2 0.509587 390133 2 -12.8742
2 0.5071 401371 3 -12.9026
2 0.509743 414714 4 -12.9353
2 0.509687 414834 5 -12.9356
2 0.509612 416680 6 -12.9401
2 0.508023 417546 7 -12.9421
2 0.509075 418182 8 -12.9437
2 0.506652 418547 9 -12.9445
2 0.507339 420637 10 -12.9495
2 0.50732 422469 11 -12.9539
2 0.507837 424256 12 -12.9581
2 0.508078 425987 13 -12.9622
2 0.508132 428399 14 -12.9678
2 0.508504 430053 15 -12.9717
2 0.508837 431846 16 -12.9758
2 0.508694 432445 17 -12.9772
2 0.50948 440847 18 -12.9965
2 0.50791 444696 19 -13.0051
2 0.510156 450407 20 -13.0179
2 0.50776 481205 21 -13.084
2 0.507055 543345 22 -13.2055
2 0.509497 593743 23 -13.2942
2 0.5076 624993 24 -13.3455
2 0.508141 656326 25 -13.3944
2 0.50747 680281 26 -13.4303
2 0.506559 710591 27 -13.4739
2 0.506336 769857 28 -13.554
2 0.505188 792498 29 -13.5829
2 0.505506 848075 30 -13.6507
2 0.505668 877413 31 -13.6847
2 0.506971 894319 32 -13.7038
2 0.50687 959986 33 -13.7747
2 0.504709 971492 34 -13.7866
2 0.50443 998693 35 -13.8142
2 0.505614 1015744 36 -13.8311
2 0.505651 1200156 37 -13.998
2 0.506365 1239126 38 -14.0299
2 0.505056 1311868 39 -14.087
2 0.504861 1367832 40 -14.1287
2 0.504283 1515202 41 -14.2311
3 0.504684 1523758 1 -14.2367
2 0.504715 1704787 42 -14.349
3 0.503862 1730914 2 -14.3642
3 0.503662 1759525 3 -14.3806
2 0.504092 1773853 43 -14.3887
3 0.504362 1797641 4 -14.402
3 0.503497 1807224 5 -14.4073
3 0.504222 1870060 6 -14.4415
3 0.504066 1873321 7 -14.4432
3 0.503871 1876162 8 -14.4447
3 0.503604 1934341 9 -14.4753
3 0.503887 1934343 10 -14.4753
3 0.50337 2003323 11 -14.5103
2 0.503775 2060992 44 -14.5387
2 0.504305 2259123 45 -14.6305
2 0.50431 2334501 46 -14.6633
2 0.50355 2405667 47 -14.6933
2 0.504655 2421855 48 -14.7
3 0.503417 2426453 12 -14.7019
2 0.503506 2866216 49 -14.8685
3 0.503097 3262642 13 -14.998
3 0.50259 3542804 14 -15.0804
3 0.502631 3764201 15 -15.141
3 0.502326 3888634 16 -15.1736
2 0.498833 4459034 50 -15.3104
3 0.502975 4552828 17 -15.3313
3 0.502596 4885742 18 -15.4018
3 0.502206 4886907 19 -15.4021
3 0.502656 4964395 20 -15.4178
3 0.502427 5006541 21 -15.4263
3 0.502285 5042936 22 -15.4335
3 0.502792 5070941 23 -15.439
3 0.502251 5092757 24 -15.4433
3 0.502159 5690920 25 -15.5544
3 0.502344 5738014 26 -15.5626
3 0.502551 5759395 27 -15.5663
3 0.50202 6010623 28 -15.609
3 0.502503 6475722 29 -15.6836
3 0.502298 6757249 30 -15.7261
3 0.502295 6917842 31 -15.7496
3 0.502142 7257896 32 -15.7976
3 0.501999 7391528 33 -15.8158
3 0.501976 7612727 34 -15.8453
3 0.502034 7616080 35 -15.8458
3 0.50155 8236494 36 -15.9241
3 0.502199 8860897 37 -15.9972
3 0.501999 9483846 38 -16.0651
3 0.501278 10538303 39 -16.1705
3 0.50167 11221105 40 -16.2333
3 0.50148 11471397 41 -16.2554
3 0.501467 11804481 42 -16.284
3 0.501606 12425605 43 -16.3353
3 0.501417 15025228 44 -16.5252
3 0.5015 17329778 45 -16.6679
3 0.501611 19010209 46 -16.7605
3 0.50145 19645397 47 -16.7934
3 0.501081 30562878 48 -17.2353
3 0.50101 33547749 49 -17.3285
3 0.500982 40156426 50 -17.5083