ADSTGCN: A Dynamic Adaptive Deeper Spatio-Temporal Graph Convolutional Network for Multi-Step Traffic Forecasting

Multi-step traffic forecasting has always been extremely challenging due to constantly changing traffic conditions. Advanced Graph Convolutional Networks (GCNs) are widely used to extract spatial information from traffic networks. Existing GCNs for traffic forecasting are usually shallow networks th...

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Detalhes bibliográficos

Principais autores:	Zhengyan Cui, Junjun Zhang, Giseop Noh, Hyun Jun Park
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2023-08-01
coleção:	Sensors
Assuntos:	traffic forecasting spatio-temporal graph deep graph convolutional network adaptive graph construction
Acesso em linha:	https://www.mdpi.com/1424-8220/23/15/6950
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