Predicting Shear Strength in FRP-Reinforced Concrete Beams Using Bat Algorithm-Based Artificial Neural Network

Table 9

Final weights and bias values for the optimized ANN-BAT 2L (12-5) model 6-12-5-1.

IW												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