Estimation of Container Traffic at Seaports by Using Several Soft Computing Methods: A Case of Turkish Seaports

Table 3

Performances of the best performing models of each seaport.

Seaports	Model type	Training period			Testing period			values
			RMSE (×10^3 TEU)	MAPE (%)		RMSE (×10^3 TEU)	MAPE (%)
Istanbul seaports	ANN-ABC (3, 8, 1)	0.966	66.32	1.91	0.962	210.26	6.04	0.813
	LSSVM	0.976	120.14	3.31	0.974	165.02	4.54	0.959
	MNR-GA	0.956	165.44	5.46	0.852	400.01	13.20	0.234
	ANN-LM	0.985	102.14	2.06	0.947	208.33	4.99	0.861
Izmir seaports	ANN-ABC (3, 12, 1)	0.992	17.90	3.49	0.949	38.02	4.01	0.859
	LSSVM	0.986	24.48	2.43	0.964	33.69	2.93	0.878
	MNR-GA	0.929	57.38	3.71	0.963	71.67	6.13	0.573
	ANN-LM	0.985	36.54	3.38	0.964	44.70	5.03	0.675
Mersin seaport	ANN-ABC (3, 8, 1)	0.995	21.11	1.39	0.972	56.68	3.46	0.718
	LSSVM	0.984	40.65	2.50	0.960	63.32	3.78	0.636
	MNR-GA	0.982	61.57	4.75	0.806	135.42	9.25	0.508
	ANN-LM	0.988	30.13	2.55	0.981	60.08	3.07	0.771

models were denoted as LSSVM (regulation constant, kernel parameter).