Data driven hybrid fuzzy model for short-term traffic flow prediction-Reference-Cited by-同舟云学术

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Data driven hybrid fuzzy model for short-term traffic flow prediction

Published:2018-12-24 Issue:6 Volume:35 Page:6525-6536
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Li Chengdong¹,Yan Bingyang¹,Tang Minjia¹,Yi Jianqiang²,Zhang Xiqiao³

Affiliation:

1. School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan, China

2. Institute of Automation, Chinese Academy of Sciences, Beijing, China

3. School of Transportation Science and Technology, Harbin Institute of Technology, Harbin, China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference52 articles.

1. Social media based transportation research: the state of the work and the networking

2. An efficient realization of deep learning for traffic data imputation;Duan;Transportation Research Part C: Emerging Technologies,2016

3. Traffic signal timing via deep reinforcement learning;Li;IEEE/CAA Journal of Automatica Sinica,2016

4. Urban com-puting: Concepts, methodologies, and applications;Zheng;ACM Transactions on Intelligent Systems and Technology,2014

5. Effective and efficient: Large-scale dynamic city express;Zhang;IEEE Transactions on Knowledge and Data Engineering,2016

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