Predicting Traffic Flow Using Dynamic Spatial-Temporal Graph Convolution Networks

Traffic flow prediction plays a key role in the construction of intelligent transportation system. However, due to its complex spatio-temporal dependence and its uncertainty, the research becomes very challenging. Most of the existing studies are based on graph neural networks that model traffic flo...

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Veröffentlicht in:	Computers, materials & continua Jg. 78; H. 3; S. 4343 - 4361
Hauptverfasser:	Liu, Yunchang, Wan, Fei, Liang, Chengwu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Henderson Tech Science Press 2024
Schlagworte:	Algorithms Artificial neural networks Convolution Flow graphs Graph neural networks Intelligent transportation systems Nodes Predictions Spatiotemporal data Traffic flow Traffic models Transportation networks
ISSN:	1546-2226, 1546-2218, 1546-2226
Online-Zugang:	Volltext
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