Table 3.

Performance comparison of different approaches on four datasets.

	PEMS03			PEMS04			PEMS07			PEMS08
	RMSE	MAE	MAPE	RMSE	MAE	MAPE	RMSE	MAE	MAPE	RMSE	MAE	MAPE
STG-NCDE	27.09	15.57	15.06	31.09	19.21	12.76	33.84	20.53	8.80	24.81	15.45	9.92
ST-aware	26.63	15.17	15.83	31.02	19.06	12.52	34.05	20.74	8.77	24.62	15.41	9.94
DSTAGNN	27.21	15.57	14.68	31.46	19.30	12.70	34.51	21.42	9.01	24.77	15.67	9.94
Auto-DSTSGN	25.17	14.59	14.22	30.48	18.85	13.21	33.02	20.08	8.57	23.76	14.74	9.45
PDFormer	25.39	14.94	15.82	29.97	18.32	12.10	32.87	19.83	8.53	23.51	13.58	9.05
STGSA	27.89	15.36	14.45	31.30	19.32	12.90	34.30	20.80	8.86	24.28	15.26	9.81
ISTNet	25.14	15.12	15.43	30.46	18.54	12.52	33.06	19.79	8.77	23.39	14.13	9.43
DeepSTUQ	26.77	15.13	14.03	31.68	19.11	12.71	33.71	20.36	8.63	24.60	15.44	10.06
STJGCN	25.70	14.92	14.81	30.35	18.81	11.92	33.01	19.95	8.31	23.74	14.53	9.15
DEC-Former	23.55	14.33	14.27	29.24	18.23	12.04	33.04	19.48	8.54	23.06	13.23	9.12
STD-MAE	24.43	13.80	13.96	29.25	17.80	11.97	31.44	18.65	7.84	22.47	13.44	8.76
STGMS	22.22	12.87	13.17	24.48	14.89	10.86	24.09	14.61	6.78	17.52	10.87	7.61
Improved(%)	9.05	6.75	5.66	16.28	16.35	8.89	23.38	21.66	13.52	22.03	17.84	13.13