Spatio-Temporal AutoEncoder for Traffic Flow Prediction

Forecasting traffic flow is an important task in urban areas, and a large number of methods have been proposed for traffic flow prediction. However, most of the existing methods follow a general technical route to aggregate historical information spatially and temporally. In this paper, we propose a...

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Veröffentlicht in:	IEEE transactions on intelligent transportation systems Jg. 24; H. 5; S. 1 - 11
Hauptverfasser:	Liu, Mingzhe, Zhu, Tongyu, Ye, Junchen, Meng, Qingxin, Sun, Leilei, Du, Bowen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.05.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Convolution Correlation Data mining Decoding Feature extraction hidden state extraction History Spatial distribution spatio-temporal autoencoder Time series analysis Traffic flow Traffic flow prediction Traffic information Urban areas
ISSN:	1524-9050, 1558-0016
Online-Zugang:	Volltext
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