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A temporal-aware LSTM enhanced by loss-switch mechanism for traffic flow forecasting

  • Published:2021-02 Issue: Volume:427 Page:169-178
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Lu Huakang,Ge Zuhao,Song Youyi,Jiang Dazhi,Zhou Teng,Qin Jing

Funder

Department of Education of Guangdong Province

Special Fund Project for Science and Technology Innovation Strategy of Guangdong Province

National Natural Science Foundation of China

Hong Kong Polytechnic University

Li Ka Shing Foundation

Natural Science Foundation of Guangdong Province

Shantou University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference45 articles.

1. Eco-routing navigation system based on multisource historical and real-time traffic information;Boriboonsomsin;IEEE Trans. Intell. Transp. Syst.,2012

2. A deterministic and stochastic petri net model for traffic-responsive signaling control in urban areas;Di Febbraro;IEEE Trans. Intell. Transp. Syst.,2016

3. A multi-agent advanced traveler information system for optimal trip planning in a co-modal framework;Dotoli;IEEE Trans. Intell. Transp. Syst.,2017

4. Hybrid dual kalman filtering model for short-term traffic flow forecasting;Zhou;IET Intel. Transport Syst.,2019

5. A noise-immune kalman filter for short-term traffic flow forecasting;Cai;Physica A,2019

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