TGAE: Temporal Graph Autoencoder for Travel Forecasting

With the development of intelligent transportation systems, timely and accurate travel forecasting task has witnessed growing interest. Unlike most previous research that only considers the demand prediction in origin regions, this task aims to predict the origin-destination demand between all-regio...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems Jg. 24; H. 8; S. 1 - 13
Hauptverfasser:	Wang, Qiang, Jiang, Hao, Qiu, Meikang, Liu, Yifeng, Ye, Dongsheng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	demand prediction Forecasting Graph neural networks Graph theory Heuristic algorithms Intelligent transportation systems Links Optimization origin-destination Peer-to-peer computing Predictive models Task analysis temporal graph autoencoder temporal networks Traffic information Traffic management Transportation Transportation networks Travel forecasting Vehicle dynamics
ISSN:	1524-9050, 1558-0016
Online-Zugang:	Volltext
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