Traffic flow prediction by an ensemble framework with data denoising and deep learning model-Reference-Cited by-同舟云学术

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Traffic flow prediction by an ensemble framework with data denoising and deep learning model

Published:2021-03 Issue: Volume:565 Page:125574
ISSN:0378-4371
Container-title:Physica A: Statistical Mechanics and its Applications
language:en
Short-container-title:Physica A: Statistical Mechanics and its Applications

Author:

Chen Xinqiang,Chen Huixing,Yang Yongsheng,Wu Huafeng,Zhang Wenhui,Zhao Jiansen,Xiong Yong

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Shanghai Committee of Science and Technology, China

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Statistics and Probability

Reference38 articles.

1. An effective spatial–temporal attention based neural network for traffic flow prediction;Do;Transp. Res. C,2019

2. Controller independent software-in-the-loop approach to evaluate rule-based traffic signal retiming strategy by utilizing floating car data;Sharma;IEEE Trans. Intell. Transp. Syst.,2019

3. Markov chains based route travel time estimation considering link spatio-temporal correlation;Tang;Physica A,2020

4. Robust visual ship tracking with an ensemble framework via multi-view learning and wavelet filter;Chen;Sensors (Basel),2020

5. Identifying activities and trips with GPS data;Fang;IET Intell. Transp. Syst.,2018

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