sAMDGCN: sLSTM-Attention-Based Multi-Head Dynamic Graph Convolutional Network for Traffic Flow Forecasting

Accurate traffic flow prediction plays a vital role in intelligent transportation systems, helping traffic management departments maintain stable traffic order, reduce traffic congestion, and improve road safety. Existing prediction methods focus on dynamic modeling of the spatiotemporal dependencie...

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Auteurs principaux:	Shiyuan Zhang, Yanni Ju, Weishan Kong, Hong Qu, Liwei Huang
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2025-01-01
Collection:	Mathematics
Sujets:	traffic flow prediction spatiotemporal dependency sLSTM attention graph convolutional network
Accès en ligne:	https://www.mdpi.com/2227-7390/13/2/185
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