Traffic flow prediction based on spatial-temporal multi factor fusion graph convolutional networks

Abstract Recently, graph convolutional networks (GCNs) have become one of the important models for solving traffic flow prediction, but existing models still have two problems: (1) insufficient information utilization: there is a lack of adequate consideration of the relevant characteristic informat...

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Bibliographic Details

Published in:	Scientific Reports
Main Authors:	Ying-Ting Chen, An Liu, Cheng Li, Shuang Li, Xiao Yang
Format:	Article
Language:	English
Published:	Nature Portfolio 2025-04-01
Subjects:	Traffic flow prediction Graph convolutional network Spatial-temporal features Multi factor fusion
Online Access:	https://doi.org/10.1038/s41598-025-96801-1