研究文章
预测FRP-Reinforced混凝土梁抗剪强度使用蝙蝠算法人工神经网络
表9
最终权重和偏置值优化ANN-BAT 2 l(后))模型6-12-5-1。
|
| 信息战 |
|
|
|
|
|
|
b1 |
| 0.4204 |
0.2619 |
0.2213 |
0.0161 |
0.2935 |
0.1648 |
0.0739 |
| −0.1767 |
−0.0126 |
0.5506 |
0.7461 |
1.0547 |
−0.2850 |
−0.7219 |
| −0.0935 |
−0.8601 |
0.2501 |
0.0977 |
−0.2429 |
−0.5033 |
−0.1321 |
| 0.5766 |
−0.2759 |
0.5217 |
0.1596 |
−0.9188 |
−0.7073 |
0.3617 |
| 0.9171 |
0.1178 |
−0.3768 |
0.2166 |
0.6056 |
0.7996 |
−0.7331 |
| −0.3815 |
0.9628 |
0.3432 |
0.3586 |
−0.3698 |
0.1713 |
0.8099 |
| −1.0985 |
0.2508 |
−0.6516 |
0.7722 |
−0.7020 |
−0.0241 |
−1.0067 |
| 0.3690 |
0.9792 |
0.4658 |
0.5711 |
0.8705 |
−0.4801 |
−0.4421 |
| 0.1206 |
−0.2852 |
0.1240 |
1.5382 |
−0.4439 |
0.1159 |
0.6865 |
| 0.8449 |
0.9581 |
0.5333 |
0.2143 |
0.6084 |
−0.2831 |
0.3670 |
| −0.5709 |
−0.5262 |
0.6664 |
−0.4574 |
0.5272 |
0.6221 |
−0.7244 |
| −0.1940 |
−0.4716 |
0.9008 |
0.8131 |
−0.8359 |
0.1678 |
−0.8964 |
| LW1 |
b2 |
| −0.9106 |
−0.5498 |
0.1001 |
0.3170 |
−0.3867 |
−0.0270 |
0.2159 |
0.1310 |
−0.8435 |
−0.5967 |
−0.0153 |
−0.4711 |
0.8855 |
| 0.5996 |
0.2994 |
−0.8976 |
−0.5387 |
−0.1527 |
−0.6867 |
−0.7396 |
−0.5912 |
−1.6238 |
0.0733 |
0.2830 |
0.0238 |
−0.9662 |
| −0.6558 |
−1.0271 |
−0.8346 |
−0.2157 |
−0.9100 |
−0.7549 |
0.0454 |
0.2270 |
0.7232 |
−0.9243 |
0.1531 |
−0.3032 |
−0.0690 |
| 0.4121 |
0.2851 |
−0.0533 |
0.8826 |
0.6117 |
−0.3530 |
0.6867 |
−0.8073 |
−0.1895 |
0.7869 |
−0.2941 |
0.1125 |
−0.7400 |
| −0.6563 |
0.5328 |
−0.2316 |
0.6435 |
−0.1223 |
0.1556 |
−0.4176 |
0.6846 |
−0.4174 |
−0.9972 |
0.3888 |
0.6416 |
0.9518 |
| LW2 |
|
|
|
|
|
|
|
b3 |
| 0.5901 |
1.1812 |
−0.4576 |
−0.4174 |
−0.0902 |
−0.1794 |
|
|
