Table 5.

The RMSE and RMSEm values for the best model estimated from artificial data.

Noise	Scenario	DASA		PSO		DE		A717
		RMSE	RMSEm	RMSE	RMSEm	RMSE	RMSEm	RMSE	RMSEm
	CO	0.0345	0.0345	0.0430	0.0430	0.0064	0.0064	0.6080	0.6080
0%	AO	0.0446	6.0913	0.0406	0.7693	0.0043	1.1807	0.4644	21.3690
	TO	0.0468	1.0964	0.0447	0.0877	0.0110	0.1074	0.4542	0.6150
	NPO	0.2382	2.5430	0.3198	1.9977	0.1774	12.2287	0.6220	3.0273
	CO	0.1064	0.1064	0.1072	0.1072	0.0977	0.0977	0.5363	0.5362
5%	AO	0.0739	0.3343	0.0803	1.8387	0.0678	0.2424	0.3570	0.3723
	TO	0.1139	0.1246	0.1096	0.1639	0.0985	0.5058	0.4007	0.9028
	NPO	0.2562	3.0161	0.3349	1.4970	0.2163	318.415	0.5189	1.9670
	CO	0.3926	0.3926	0.3925	0.3925	0.3904	0.3904	0.6490	0.6490
20%	AO	0.2742	1.3904	0.2735	0.4750	0.2704	1.6916	0.4680	0.6220
	TO	0.3948	0.4568	0.3955	0.4368	0.3913	0.3954	0.5698	1.2933
	NPO	0.4616	1.8011	0.5055	2.6218	0.4448	5.4207	0.7556	7.2268

The table presents the RMSE and corresponding RMSEm values for the model simulated with the best parameters obtained by parameter estimation with the four optimization methods from artificial data. The best values for RMSE are marked in bold, while the best values for RMSEm are marked in italic.