Table 3.

Error between the simulation and the actual data.

Season	Model	N∗	MAE	RMSE	MAPE
2014–2015	MAS model 1	500	4.00	5.18	55.7%
	MAS model 2	129	3.58	5.09	58.7%
	MAS model 3	43	3.25	4.79	45.3%
	MAS model 4	45	6.23	8.32	94.9%
	SIR model	N/A	15.4	19.3	438%
2015–2016	MAS model 1	500	2.54	3.55	41.9%
	MAS model 2	146	3.87	5.19	73.0%
	MAS model 3	61	5.48	8.34	64.0%
	MAS model 4	46	2.99	3.76	89.7%
	SIR model	N/A	16.9	20.7	921%
2016–2017	MAS model 1	500	9.76	12.1	89.2%
	MAS model 2	97	7.29	10.3	50.5%
	MAS model 3	30	7.14	10.0	49.4%
	MAS model 4	19	3.92	4.52	52.3%
	SIR model	N/A	8.90	12.5	66.6%
2017–2018	MAS model 1	500	9.80	17.0	45.8%
	MAS model 2	99	8.44	15.9	33.7%
	MAS model 3	37	8.29	15.6	38.0%
	MAS model 4	13	3.98	5.83	35.9%
	SIR model	N/A	16.2	21.0	393%
2018–2019	MAS model 1	500	8.41	14.2	118%
	MAS model 2	148	8.85	15.4	122%
	MAS model 3	44	8.46	15.4	113%
	MAS model 4	23	7.49	10.9	132%
	SIR model	N/A	21.9	26.6	925%

MAE, mean absolute error; MAPE, mean absolute percentage error; MAS, multi-agent system; RMSE, root mean squared error.

^∗Number of simulations included in the model.