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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Bibliographic Details

Published in:	2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS) pp. 125 - 132
Main Authors:	Ali, Ahmad, Zhu, Yanmin, Chen, Qiuxia, Yu, Jiadi, Cai, Haibin
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2019
Subjects:	Convolutional neural network crowd flows prediction Deep learning Long short term memory Spatio-temporal dynamics
Online Access:	Get full text
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