Table 12.

MAPE, MAE, and RMSE of each model

Model	Paris			Amsterdam			Lisbon
	MAPE (%)	MAE	RMSE	MAPE (%)	MAE	RMSE	MAPE (%)	MAE	RMSE
BPNN	8.63	244,662	324,617	10.12	170,141	252,206	11.04	84,110	101,228
ARIMAX	11.35	290,161	313,770	15.02	220,252	260,200	11.87	86,332	110,578
SARIMAX	9.60	257,740	321,591	15.58	251,838	367,665	12.26	94,907	108,025
SVM	10.84	301,825	459,945	6.47	106,071	139,231	6.99	56,588	84,579
LSTM	7.43	200,888	242,408	9.52	154,130	193,138	8.46	64,195	82,839
GA-TFT	6.61	174,910	224,792	5.24	87,321	102,849	4.39	35,918	43,197
DE-TFT	3.32	86,347	94,911	5.99	98,611	129,738	3.59	30,844	47,916
ADE-TFT	3.10	76,826	89,724	4.76	83,398	135,584	3.02	24,442	32,532

The bold values denote the best prediction performance of all models