TFGCRN: Temporal–Frequency Graph Convolutional Recurrent Network for Incomplete Traffic Forecasting

Traffic forecasting is a crucial component that underpins an intelligent transportation system. Among the current mainstream forecasting algorithms, spatial–temporal graph neural networks (STGNNs), as the mainstream solution, have been used in traffic forecasting due to their ability to model spatia...

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Autors principals:	Jiazhan Hu, Tao Feng
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2025-12-01
Col·lecció:	Mathematics
Matèries:	incomplete traffic forecasting intelligent transportation system spatial-temporal graph neural networks algorithms
Accés en línia:	https://www.mdpi.com/2227-7390/13/24/4003
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