Hierarchical Dynamic Spatio-Temporal Graph Convolutional Networks with Self-Supervised Learning for Traffic Flow Forecasting

It is crucial for both traffic management organisations and individual commuters to be able to forecast traffic flows accurately. Graph neural networks made great strides in this field owing to their exceptional capacity to capture spatial correlations. However, existing approaches predominantly foc...

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Autors principals:	Siwei Wei, Yanan Song, Donghua Liu, Sichen Shen, Rong Gao, Chunzhi Wang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-09-01
Col·lecció:	Inventions
Matèries:	dynamic spatio-temporal graph regional graph self-supervised learning clustering traffic flow forecasting
Accés en línia:	https://www.mdpi.com/2411-5134/9/5/102
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