Leveraging Spatio-Temporal Patterns for Predicting Citywide Traffic Crowd Flows Using Deep Hybrid Neural Networks

Predicting the accurate traffic crowd flows is of practical importance for intelligent transportation systems (ITS). However, it is challenging because traffic flows are affected by multiple complex factors, such as spatial and temporal dependencies of regions and external factors. In this paper, we...

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Veröffentlicht in:	2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS) S. 125 - 132
Hauptverfasser:	Ali, Ahmad, Zhu, Yanmin, Chen, Qiuxia, Yu, Jiadi, Cai, Haibin
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2019
Schlagworte:	Convolutional neural network crowd flows prediction Deep learning Long short term memory Spatio-temporal dynamics
Online-Zugang:	Volltext
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