| r1 |
r2 |
||
| <1 |
<1 |
吸引子 |
c |
| >1 |
>1 |
排斥子 |
p |
| >1 |
<1 |
鞍点 |
a |
| <1 |
>1 |
反鞍点 |
fa |
构造一个网络
d2（ x(a||fa) || y(a||c) ）-4-4-2-（2*k）,k∈{0,1} ，x+y=1
进样可能是x倍的a和fa组合,或者y倍的a和c组合，网络结构是4*4*2，让a向1，0收敛，让fa或c向0，1收敛。让x+y=1。
测试集在0，1位100%的p。
测试集是固定的，训练集的比例是变动的，观察x，y对网络分类性能的影响。
这个网络的收敛标准是
if (Math.abs(f2[0]-y[0])< δ && Math.abs(f2[1]-y[1])< δ )
尝试了δ从0.5到1e-6在内的26个值.
| 具体进样顺序 |
||||
| 进样顺序 |
迭代次数 |
|||
| δ=0.5 |
||||
| x(a||fa)||y(a||c) |
1，2 |
判断是否达到收敛 |
||
| 梯度下降 |
||||
| x(a||fa)||y(a||c) |
3，4 |
判断是否达到收敛 |
||
| 梯度下降 |
||||
| …… |
||||
| 达到收敛标准测量准确率,记录迭代次数，将这个过程重复199次 |
||||
| δ=0.4 |
||||
| … |
||||
| δ=1e-6 |
||||
得到的数据
| δ |
||||||||||||
| a |
fa |
1 |
0.9 |
0.8 |
0.7 |
0.6 |
0.5 |
0.4 |
0.3 |
0.2 |
0.1 |
0 |
| a |
c |
0 |
0.1 |
0.2 |
0.3 |
0.4 |
0.5 |
0.6 |
0.7 |
0.8 |
0.9 |
1 |
| 0.5 |
0.44588 |
0.45022 |
0.32894 |
0.24683 |
0.11291 |
0.11512 |
0.03597 |
0.0311 |
0.01417 |
0.01011 |
0 |
|
| 0.4 |
0.52028 |
0.52812 |
0.57773 |
0.56226 |
0.57428 |
0.56271 |
0.54622 |
0.53804 |
0.48635 |
0.47534 |
0.4654 |
|
| p |
0.3 |
0.49681 |
0.5514 |
0.58685 |
0.62591 |
0.64631 |
0.6751 |
0.67359 |
0.68461 |
0.66206 |
0.66526 |
0.7091 |
| 0.2 |
0.50802 |
0.56838 |
0.63054 |
0.65494 |
0.70204 |
0.71924 |
0.73754 |
0.74053 |
0.755 |
0.76093 |
0.81201 |
|
| 0.1 |
0.50178 |
0.59084 |
0.65361 |
0.6975 |
0.74633 |
0.76998 |
0.7966 |
0.81175 |
0.81593 |
0.82646 |
0.86962 |
|
| 0.01 |
0.49582 |
0.67679 |
0.74343 |
0.7851 |
0.82071 |
0.84327 |
0.8629 |
0.8741 |
0.88365 |
0.88848 |
0.9292 |
|
| 0.001 |
0.49319 |
0.73419 |
0.78728 |
0.83752 |
0.85759 |
0.87664 |
0.88819 |
0.89449 |
0.89978 |
0.90805 |
0.9449 |
|
| 1E-04 |
0.50209 |
0.76548 |
0.81411 |
0.84136 |
0.86212 |
0.87197 |
0.89272 |
0.89352 |
0.90319 |
0.8986 |
0.93876 |
|
| 9E-05 |
0.4932 |
0.7649 |
0.8205 |
0.85276 |
0.86098 |
0.88058 |
0.88292 |
0.89535 |
0.90353 |
0.90084 |
0.93174 |
|
| 8E-05 |
0.49773 |
0.77015 |
0.81775 |
0.83731 |
0.86305 |
0.87634 |
0.89125 |
0.89529 |
0.9075 |
0.90114 |
0.93209 |
|
| 7E-05 |
0.49551 |
0.7672 |
0.81861 |
0.84337 |
0.8618 |
0.87037 |
0.88483 |
0.8963 |
0.90331 |
0.90184 |
0.93454 |
|
| 6E-05 |
0.50421 |
0.76373 |
0.81248 |
0.84394 |
0.85376 |
0.87508 |
0.88851 |
0.89856 |
0.90574 |
0.89944 |
0.93109 |
|
| 5E-05 |
0.49854 |
0.77061 |
0.80627 |
0.84627 |
0.86156 |
0.87611 |
0.88957 |
0.89384 |
0.89862 |
0.90686 |
0.93405 |
|
| 0.00004 |
0.48881 |
0.77312 |
0.80831 |
0.8332 |
0.85962 |
0.87353 |
0.8851 |
0.90074 |
0.90584 |
0.91051 |
0.93205 |
|
| 3E-05 |
0.50209 |
0.76434 |
0.8174 |
0.8452 |
0.86985 |
0.87004 |
0.8886 |
0.89036 |
0.89856 |
0.89097 |
0.93109 |
|
| 0.00002 |
0.5058 |
0.76266 |
0.80944 |
0.8311 |
0.85292 |
0.87174 |
0.88378 |
0.88588 |
0.9015 |
0.89695 |
0.93145 |
|
| 0.00001 |
0.50192 |
0.76407 |
0.80132 |
0.8333 |
0.85989 |
0.86978 |
0.88523 |
0.88995 |
0.89636 |
0.90115 |
0.93569 |
|
| 9E-06 |
0.50408 |
0.76325 |
0.80699 |
0.83221 |
0.85096 |
0.87095 |
0.87777 |
0.89079 |
0.89506 |
0.89588 |
0.93397 |
|
| 8E-06 |
0.50188 |
0.75455 |
0.80558 |
0.83504 |
0.855 |
0.86698 |
0.87943 |
0.88833 |
0.89732 |
0.89039 |
0.9375 |
|
| 7E-06 |
0.49782 |
0.75839 |
0.80228 |
0.83528 |
0.85845 |
0.8742 |
0.88515 |
0.89104 |
0.89008 |
0.89285 |
0.93388 |
|
| 6E-06 |
0.49738 |
0.75785 |
0.80408 |
0.82737 |
0.85749 |
0.86809 |
0.88058 |
0.88697 |
0.89767 |
0.89526 |
0.93438 |
|
| 5E-06 |
0.49136 |
0.75934 |
0.79688 |
0.82396 |
0.8476 |
0.86955 |
0.88131 |
0.89367 |
0.89572 |
0.88839 |
0.94185 |
|
| 4E-06 |
0.49217 |
0.74927 |
0.79003 |
0.82463 |
0.8469 |
0.86969 |
0.88015 |
0.8876 |
0.894 |
0.88987 |
0.943 |
|
| 3E-06 |
0.5033 |
0.74714 |
0.80018 |
0.82504 |
0.85333 |
0.86856 |
0.87966 |
0.88051 |
0.89376 |
0.88503 |
0.94163 |
|
| 2E-06 |
0.50593 |
0.7406 |
0.79291 |
0.82347 |
0.84607 |
0.86327 |
0.87254 |
0.89193 |
0.89195 |
0.88841 |
0.94214 |
|
| 1E-06 |
0.49536 |
0.75413 |
0.79126 |
0.82011 |
0.85432 |
0.85613 |
0.87883 |
0.88007 |
0.89488 |
0.88014 |
0.93318 |
|
| 平均值 |
0.49912 |
0.75486 |
0.79915 |
0.82804 |
0.853 |
0.86772 |
0.88007 |
0.88808 |
0.89468 |
0.89074 |
0.93772 |
观察准确率的图像
在δ<1e-5以后是很稳定的，将1e-6<δ<1e-5的准确率取平均值得到图像
由《B*P神经网络分类22对角矩阵准确率数据汇总》得到的表格可以查到
| p |
p |
|||
| c |
p |
0 |
1 |
0.258402 |
| c |
p |
1 |
0 |
0.740507 |
| a |
p |
0 |
1 |
0.864001 |
| a |
p |
1 |
0 |
0.136366 |
| c |
a |
0 |
1 |
0.063246 |
| c |
a |
1 |
0 |
0.93631 |
| a |
fa |
0 |
1 |
0.49912 |
| a |
fa |
1 |
0 |
0.500347 |
| p |
fa |
0 |
1 |
0.135043 |
| p |
fa |
1 |
0 |
0.865318 |
| c |
fa |
0 |
1 |
0.064735 |
| c |
fa |
1 |
0 |
0.935863 |
测试集a||fa对0，1位置的p的分类准确率是0.49912，a||c对0，1位置p的分类准确率是0.93631，但是得到的并不是一条直线，表明输入对象fa||c之间存在相互作用，对结果有影响。
| a |
fa |
a |
c |
pb0 |
1 |
0.93631 |
0.49912 |
0.935863 |
1 |
0.49912 |
0.754857 |
0.799151 |
0.82804 |
0.852999 |
0.86772 |
0.880065 |
0.888085 |
0.894681 |
0.890737 |
0.937723 |
||
| a |
fa |
a |
c |
pb1 |
2 |
0.063246 |
0.500347 |
0.064735 |
2 |
0.50088 |
0.245143 |
0.200849 |
0.17196 |
0.147001 |
0.13228 |
0.119935 |
0.111915 |
0.105319 |
0.109263 |
0.062277 |
||
| a |
fa |
a |
c |
cb0 |
3 |
0.93874 |
0.500403 |
0.938718 |
3 |
0.500403 |
0.717344 |
0.768623 |
0.798632 |
0.819687 |
0.835527 |
0.849605 |
0.859516 |
0.867684 |
0.869758 |
0.93874 |
||
| a |
fa |
a |
c |
cb1 |
4 |
0.061631 |
0.500046 |
0.060715 |
4 |
0.499597 |
0.282656 |
0.231377 |
0.201368 |
0.180313 |
0.164473 |
0.150395 |
0.140484 |
0.132316 |
0.130242 |
0.06126 |
||
| a |
fa |
a |
c |
ab0 |
5 |
0.198454 |
0.000348 |
0 |
5 |
0.000348 |
0.033511 |
0.052534 |
0.067696 |
0.08233 |
0.094839 |
0.106371 |
0.113552 |
0.119355 |
0.122333 |
0.198454 |
||
| a |
fa |
a |
c |
ab1 |
6 |
0.800701 |
0.999621 |
1 |
6 |
0.999652 |
0.966489 |
0.947466 |
0.932304 |
0.91767 |
0.905161 |
0.893629 |
0.886448 |
0.880645 |
0.877667 |
0.801546 |
||
| a |
fa |
a |
p |
cb0 |
7 |
0.624975 |
0.500403 |
0.62563 |
7 |
0.499617 |
0.51692 |
0.522218 |
0.54357 |
0.560013 |
0.575717 |
0.587874 |
0.599967 |
0.608206 |
0.619354 |
0.624975 |
||
| a |
fa |
a |
p |
cb1 |
8 |
0.373758 |
0.500046 |
0.374131 |
8 |
0.500383 |
0.48308 |
0.477782 |
0.45643 |
0.439987 |
0.424283 |
0.412126 |
0.400033 |
0.391794 |
0.380646 |
0.375025 |
||
| a |
fa |
a |
p |
ab0 |
9 |
0.040855 |
0.000348 |
0 |
9 |
0.000394 |
0.005513 |
0.005128 |
0.009861 |
0.014368 |
0.019362 |
0.023502 |
0.027676 |
0.032474 |
0.037415 |
0.040855 |
||
| a |
fa |
a |
p |
ab1 |
10 |
0.958847 |
0.999621 |
1 |
10 |
0.999606 |
0.994487 |
0.994872 |
0.990139 |
0.985632 |
0.980638 |
0.976498 |
0.972324 |
0.967526 |
0.962585 |
0.959145 |
||
| a |
fa |
a |
p |
pb0 |
11 |
0.864001 |
0.49912 |
0.865318 |
11 |
0.50239 |
0.62861 |
0.682381 |
0.72875 |
0.762817 |
0.790262 |
0.810617 |
0.826737 |
0.842293 |
0.853794 |
0.864078 |
||
| a |
fa |
a |
p |
pb1 |
12 |
0.136366 |
0.49912 |
0.135043 |
12 |
0.49761 |
0.37139 |
0.317619 |
0.27125 |
0.237183 |
0.209738 |
0.189383 |
0.173263 |
0.157707 |
0.146206 |
0.135922 |
||
| c |
fa |
c |
p |
cb0 |
13 |
0 |
0.060715 |
0.374131 |
13 |
0.061631 |
0.000169 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
||
| c |
fa |
c |
p |
cb1 |
14 |
1 |
0.938718 |
0.374131 |
14 |
0.938369 |
0.999831 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
||
| c |
fa |
c |
p |
ab0 |
15 |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
||
| c |
fa |
c |
p |
ab1 |
16 |
0.999991 |
0.999991 |
0.999991 |
16 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
||
| p |
fa |
p |
c |
ab0 |
17 |
0.999991 |
0 |
0.999991 |
17 |
0 |
0 |
0.251756 |
0.589507 |
0.674203 |
0.777887 |
0.681938 |
0.584354 |
0.249025 |
0 |
0.999981 |
||
| p |
fa |
p |
c |
ab1 |
18 |
0 |
1 |
0 |
18 |
1 |
1 |
0.748244 |
0.410493 |
0.325797 |
0.222113 |
0.318062 |
0.415646 |
0.750975 |
1 |
1.91E-05 |
||
| c |
fa |
c |
a |
ab0 |
19 |
0.800701 |
0 |
0.000348 |
19 |
0 |
0.097396 |
0.173459 |
0.235091 |
0.288908 |
0.342857 |
0.400415 |
0.489861 |
0.802727 |
||||
| c |
fa |
c |
a |
ab1 |
20 |
0.198454 |
1 |
0.999621 |
20 |
1 |
|
0.902604 |
0.826541 |
0.764909 |
0.711092 |
0.657143 |
0.599585 |
0.510139 |
|
0.197273 |
||
| c |
p |
c |
fa |
pb0 |
21 |
0.258402 |
0.064735 |
0.865318 |
21 |
0.064883 |
0.258733 |
0.405405 |
0.502393 |
0.549853 |
0.554114 |
0.537257 |
0.523274 |
0.493078 |
0.452059 |
0.262191 |
||
| p |
fa |
p |
c |
pb1 |
22 |
0.258402 |
0.865318 |
0.935863 |
22 |
0.864149 |
0.866174 |
0.842718 |
0.839909 |
0.825159 |
0.814363 |
0.799725 |
0.767323 |
0.733453 |
0.644103 |
0.255243 |
||
| c |
p |
c |
fa |
pb1 |
23 |
0.740507 |
0.935863 |
0.135043 |
23 |
0.935117 |
0.741267 |
0.594595 |
0.497607 |
0.450147 |
0.445886 |
0.462743 |
0.476726 |
0.506922 |
0.547941 |
0.737809 |
||
| p |
fa |
p |
c |
pb0 |
24 |
0.740507 |
0.135043 |
0.064735 |
24 |
0.135851 |
0.133826 |
0.157282 |
0.160091 |
0.174841 |
0.185637 |
0.200275 |
0.232677 |
0.266547 |
0.355897 |
0.744757 |
||
| p |
fa |
p |
c |
cb0 |
25 |
1 |
0.374131 |
0.938718 |
25 |
0.374689 |
0.461328 |
0.70292 |
0.882162 |
0.957317 |
0.973871 |
0.983817 |
0.988585 |
0.994648 |
0.998053 |
1 |
||
| p |
fa |
p |
c |
cb1 |
26 |
0 |
0.62563 |
0.060715 |
26 |
0.625311 |
0.538672 |
0.29708 |
0.117838 |
0.042683 |
0.026129 |
0.016183 |
0.011415 |
0.005352 |
0.001947 |
0 |
||
为了解准确率的表达式计算了26组不同的组合
其中的第21组是比较有代表性的
| c |
p |
c |
fa |
pb0 |
21 |
0.258402 |
0.064735 |
0.865318 |
测试集c||p对0，1位的p的分类准确率是0.258，c||fa对0，1位的p的分类准确率是0.0647，但得到的准确率大于0.258，而p||fa对0，1位的p的分类准确率是0.86，表明两组训练集之间是有相互作用的。
假设准确率f（a,b,c）=xa+yb+zc ，让a和b分别是两个训试集准确率，c是相互作用项的分类准确率，求x，y，z。
解矩阵Ax=B
让A=
| a |
b |
c |
| 0.93631 |
0.49912 |
0.935863 |
| 0.063246 |
0.500347 |
0.064735 |
| 0.93874 |
0.500403 |
0.938718 |
| 0.061631 |
0.500046 |
0.060715 |
| 0.800701 |
0.999621 |
1 |
| 0.624975 |
0.500403 |
0.62563 |
| 0.373758 |
0.500046 |
0.374131 |
| 0.958847 |
0.999621 |
1 |
| 0.864001 |
0.49912 |
0.865318 |
| 0.136366 |
0.49912 |
0.135043 |
| 0.258402 |
0.064735 |
0.865318 |
| 0.258402 |
0.865318 |
0.935863 |
| 0.740507 |
0.935863 |
0.135043 |
| 0.740507 |
0.135043 |
0.064735 |
| 1 |
0.374131 |
0.938718 |
让B分别等于下面表格的第1-9列
| 1 |
0.9 |
0.8 |
0.7 |
0.6 |
0.5 |
0.4 |
0.3 |
0.2 |
0.1 |
0 |
|
| 0 |
0.1 |
0.2 |
0.3 |
0.4 |
0.5 |
0.6 |
0.7 |
0.8 |
0.9 |
1 |
|
| 1 |
0.49912 |
0.754857 |
0.799151 |
0.82804 |
0.852999 |
0.86772 |
0.880065 |
0.888085 |
0.894681 |
0.890737 |
0.937723 |
| 2 |
0.50088 |
0.245143 |
0.200849 |
0.17196 |
0.147001 |
0.13228 |
0.119935 |
0.111915 |
0.105319 |
0.109263 |
0.062277 |
| 3 |
0.500403 |
0.717344 |
0.768623 |
0.798632 |
0.819687 |
0.835527 |
0.849605 |
0.859516 |
0.867684 |
0.869758 |
0.93874 |
| 4 |
0.499597 |
0.282656 |
0.231377 |
0.201368 |
0.180313 |
0.164473 |
0.150395 |
0.140484 |
0.132316 |
0.130242 |
0.06126 |
| 6 |
0.999652 |
0.966489 |
0.947466 |
0.932304 |
0.91767 |
0.905161 |
0.893629 |
0.886448 |
0.880645 |
0.877667 |
0.801546 |
| 7 |
0.499617 |
0.51692 |
0.522218 |
0.54357 |
0.560013 |
0.575717 |
0.587874 |
0.599967 |
0.608206 |
0.619354 |
0.624975 |
| 8 |
0.500383 |
0.48308 |
0.477782 |
0.45643 |
0.439987 |
0.424283 |
0.412126 |
0.400033 |
0.391794 |
0.380646 |
0.375025 |
| 10 |
0.999606 |
0.994487 |
0.994872 |
0.990139 |
0.985632 |
0.980638 |
0.976498 |
0.972324 |
0.967526 |
0.962585 |
0.959145 |
| 11 |
0.50239 |
0.62861 |
0.682381 |
0.72875 |
0.762817 |
0.790262 |
0.810617 |
0.826737 |
0.842293 |
0.853794 |
0.864078 |
| 12 |
0.49761 |
0.37139 |
0.317619 |
0.27125 |
0.237183 |
0.209738 |
0.189383 |
0.173263 |
0.157707 |
0.146206 |
0.135922 |
| 21 |
0.064883 |
0.258733 |
0.405405 |
0.502393 |
0.549853 |
0.554114 |
0.537257 |
0.523274 |
0.493078 |
0.452059 |
0.262191 |
| 22 |
0.864149 |
0.866174 |
0.842718 |
0.839909 |
0.825159 |
0.814363 |
0.799725 |
0.767323 |
0.733453 |
0.644103 |
0.255243 |
| 23 |
0.935117 |
0.741267 |
0.594595 |
0.497607 |
0.450147 |
0.445886 |
0.462743 |
0.476726 |
0.506922 |
0.547941 |
0.737809 |
| 24 |
0.135851 |
0.133826 |
0.157282 |
0.160091 |
0.174841 |
0.185637 |
0.200275 |
0.232677 |
0.266547 |
0.355897 |
0.744757 |
| 25 |
0.374689 |
0.461328 |
0.70292 |
0.882162 |
0.957317 |
0.973871 |
0.983817 |
0.988585 |
0.994648 |
0.998053 |
1 |
可以解得
| x |
0.08595 |
0.13512 |
0.16272 |
0.19476 |
0.22421 |
0.26321 |
0.31324 |
0.37161 |
0.48366 |
| y |
0.64044 |
0.44095 |
0.30452 |
0.22251 |
0.18642 |
0.16607 |
0.14408 |
0.13176 |
0.1124 |
| z |
0.2732 |
0.4277 |
0.54119 |
0.59085 |
0.59716 |
0.58003 |
0.55157 |
0.50727 |
0.41328 |
比如第一组数据=0.93631*0.08595+0.49912*0.64044+0.935863*0.2732=0.65581
将x，y，z画成图
可以用曲线拟合x
| R |
0.1 |
0.2 |
0.3 |
0.4 |
0.5 |
0.6 |
0.7 |
0.8 |
0.9 |
| X |
0.08595 |
0.13512 |
0.16272 |
0.19476 |
0.22421 |
0.26321 |
0.31324 |
0.37161 |
0.48366 |
拟合方程式：x = a + b·r + c·r^2 + d·r^3
a = 0.0191981746031519
b = 0.787666859067049
c = -1.32153823953865
d = 1.12769360269386
相关系数 R2：0.998795559102663
| R |
0.1 |
0.2 |
0.3 |
0.4 |
0.5 |
0.6 |
0.7 |
0.8 |
0.9 |
| y |
0.64044 |
0.44095 |
0.30452 |
0.22251 |
0.18642 |
0.16607 |
0.14408 |
0.13176 |
0.1124 |
用同样的办法拟合y
拟合方程式：Y = a + b·r+ c·r^2 + d·r^3
a = 0.913671031746098
b = -3.17943332130888
c = 4.53483189033309
d = -2.21763468013543
相关系数 R2：0.999299411271458
因此准确率可以表达成
让r=0.1，0.2…0.9
拟合得到的数据
| 1 |
0.65581 |
0.74687 |
0.81083 |
0.84637 |
0.86184 |
0.87216 |
0.8814 |
0.88844 |
0.89573 |
| 2 |
0.34356 |
0.25686 |
0.19769 |
0.1619 |
0.14611 |
0.13729 |
0.12761 |
0.12227 |
0.11358 |
| 3 |
0.65762 |
0.74898 |
0.81316 |
0.84882 |
0.86432 |
0.87467 |
0.88392 |
0.89096 |
0.89823 |
| 4 |
0.34213 |
0.25479 |
0.19516 |
0.15914 |
0.14329 |
0.13448 |
0.12484 |
0.11959 |
0.11111 |
| 6 |
0.98222 |
0.97667 |
0.97588 |
0.96922 |
0.96303 |
0.95679 |
0.94641 |
0.93653 |
0.9129 |
| 7 |
0.54512 |
0.57268 |
0.59266 |
0.60272 |
0.60701 |
0.61049 |
0.61294 |
0.61554 |
0.61708 |
| 8 |
0.45459 |
0.43101 |
0.41557 |
0.40511 |
0.40043 |
0.39843 |
0.39548 |
0.39456 |
0.3916 |
| 10 |
0.99581 |
0.99804 |
1.00162 |
1.00002 |
0.99849 |
0.99842 |
0.99594 |
0.9953 |
0.98939 |
| 11 |
0.63032 |
0.70693 |
0.76088 |
0.7906 |
0.8035 |
0.81221 |
0.81984 |
0.82578 |
0.8316 |
| 12 |
0.36827 |
0.29627 |
0.24727 |
0.21741 |
0.20426 |
0.19711 |
0.18911 |
0.18494 |
0.17787 |
| 21 |
0.30007 |
0.43356 |
0.53006 |
0.576 |
0.58674 |
0.58067 |
0.56755 |
0.5435 |
0.48987 |
| 22 |
0.83207 |
0.81675 |
0.81203 |
0.79582 |
0.77811 |
0.75455 |
0.72181 |
0.68477 |
0.60901 |
| 23 |
0.6999 |
0.57048 |
0.47857 |
0.43225 |
0.42113 |
0.42866 |
0.44128 |
0.46699 |
0.51916 |
| 24 |
0.16782 |
0.18729 |
0.19665 |
0.21252 |
0.22986 |
0.25488 |
0.28712 |
0.32581 |
0.40009 |
| 25 |
0.58202 |
0.70158 |
0.78468 |
0.83265 |
0.85452 |
0.86983 |
0.88491 |
0.89709 |
0.91367 |
比较实测数据和拟合数据
| 实测 |
1 |
0.75486 |
0.79915 |
0.82804 |
0.853 |
0.86772 |
0.88007 |
0.88808 |
0.89468 |
0.89074 |
| 拟合 |
1 |
0.65581 |
0.74687 |
0.81083 |
0.84637 |
0.86184 |
0.87216 |
0.8814 |
0.88844 |
0.89573 |
| 实测 |
2 |
0.24514 |
0.20085 |
0.17196 |
0.147 |
0.13228 |
0.11993 |
0.11192 |
0.10532 |
0.10926 |
| 拟合 |
2 |
0.34356 |
0.25686 |
0.19769 |
0.1619 |
0.14611 |
0.13729 |
0.12761 |
0.12227 |
0.11358 |
用实测数据/拟合数据
| 1 |
1.15103 |
1.07 |
1.02123 |
1.00783 |
1.00683 |
1.00906 |
1.00759 |
1.00702 |
0.99443 |
| 2 |
0.71353 |
0.78194 |
0.86984 |
0.90798 |
0.90533 |
0.8736 |
0.87703 |
0.86139 |
0.96197 |
| 3 |
1.09082 |
1.02622 |
0.98214 |
0.96568 |
0.96668 |
0.97134 |
0.97239 |
0.97387 |
0.9683 |
| 4 |
0.82616 |
0.90811 |
1.0318 |
1.13303 |
1.1478 |
1.11834 |
1.1253 |
1.10643 |
1.17223 |
| 6 |
0.98399 |
0.97009 |
0.95534 |
0.94681 |
0.9399 |
0.93399 |
0.93665 |
0.94033 |
0.9614 |
| 7 |
0.94827 |
0.91188 |
0.91716 |
0.92915 |
0.94845 |
0.96296 |
0.97883 |
0.98808 |
1.00368 |
| 8 |
1.06268 |
1.10851 |
1.09833 |
1.08608 |
1.05955 |
1.03438 |
1.01151 |
0.99298 |
0.97203 |
| 10 |
0.99867 |
0.99682 |
0.98854 |
0.98561 |
0.98212 |
0.97805 |
0.97628 |
0.9721 |
0.9729 |
| 11 |
0.99728 |
0.96528 |
0.95777 |
0.96485 |
0.98353 |
0.99804 |
1.00842 |
1.01999 |
1.02669 |
| 12 |
1.00847 |
1.07206 |
1.097 |
1.09096 |
1.02681 |
0.9608 |
0.91618 |
0.85274 |
0.822 |
| 21 |
0.86223 |
0.93507 |
0.9478 |
0.9546 |
0.9444 |
0.92523 |
0.92198 |
0.90722 |
0.92281 |
| 22 |
1.04098 |
1.0318 |
1.03433 |
1.03686 |
1.04659 |
1.05988 |
1.06305 |
1.07109 |
1.05762 |
| 23 |
1.0591 |
1.04226 |
1.03978 |
1.0414 |
1.05877 |
1.07952 |
1.08032 |
1.0855 |
1.05545 |
| 24 |
0.79745 |
0.83977 |
0.81408 |
0.82271 |
0.80761 |
0.78575 |
0.81038 |
0.8181 |
0.88955 |
| 25 |
0.79264 |
1.00191 |
1.12424 |
1.14972 |
1.13967 |
1.13105 |
1.11715 |
1.10875 |
1.09236 |
从表达看到拟合精度还是有保障的。但这种办法只是对矩阵A中不含有0的元素的情况成立。
实验参数
学习率 0.1
权重初始化方式
Random rand1 =new Random();
int ti1=rand1.nextInt(98)+1;
tw[a][b]=xx*((double)ti1/100);
http://www.qinms.com/webapp/curvefit/cf.aspx
