Table 2.

Parameters estimates with respect to ${\mathrm{g}}_{\mathrm{n}}$ and ${\mathrm{p}}_{\mathrm{n}}$ at 0.05 noise level.

Methods	${\mathrm{g}}_{\mathrm{n}}$	${\mathrm{p}}_{\mathrm{n}}$	Parameters				Best Fitness
			${\mathrm{b}}_1$	${\mathrm{b}}_2$	${\mathrm{c}}_1$	${\mathrm{c}}_2$
GWO	200	10	−1.5201	0.6553	0.2973	0.2588	0.00409
		30	−1.5418	0.6695	0.2617	0.2880	0.00232
	500	10	−1.5435	0.6772	0.2232	0.3523	0.00235
		30	−1.5542	0.6810	0.2287	0.3179	0.00219
AGWO	200	10	−1.4913	0.6427	0.2357	0.3969	0.00428
		30	−1.5459	0.6733	0.2059	0.3416	0.00229
	500	10	−1.5658	0.6916	0.2346	0.3067	0.00228
		30	−1.5339	0.6619	0.2320	0.3209	0.00218
CGWO	200	10	−1.5785	0.7069	0.2165	0.3121	0.00293
		30	−1.5304	0.6617	0.2482	0.3239	0.00223
	500	10	−1.5496	0.6705	0.2117	0.2990	0.00285
		30	−1.5517	0.6775	0.2176	0.3160	0.00231
ICGWO	200	10	−1.5363	0.6676	0.3003	0.2620	0.00294
		30	−1.5345	0.6664	0.2631	0.3037	0.00226
	500	10	−1.5363	0.6675	0.2230	0.3278	0.00241
		30	−1.5495	0.6806	0.2308	0.3242	0.00222
True Parameters			−1.5300	0.6600	0.2500	0.3000	0