Uncertainty-Aware Temporal Graph Convolutional Network for Traffic Speed Forecasting

Traffic speed forecasting has been a very active research area as it is essential for Intelligent Transportation Systems. Although a plethora of deep learning methods have been proposed for traffic speed forecasting, the majority of them can only make point-wise prediction, which may not provide eno...

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Vydané v:	IEEE transactions on intelligent transportation systems Ročník 25; číslo 8; s. 8578 - 8590
Hlavní autori:	Qian, Weizhu, Nielsen, Thomas Dyhre, Zhao, Yan, Larsen, Kim Guldstrand, Yu, James Jianqiao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.08.2024
Predmet:	Convolutional neural networks Data models Deep learning Forecasting gated recurrent unit graph convolutional network Predictive models Roads spatio-temporal model Traffic speed forecasting Uncertainty uncertainty quantification
ISSN:	1524-9050, 1558-0016
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