Traffic state prediction using conditionally Gaussian observed Markov fuzzy switching model-Reference-Cited by-同舟云学术

Traffic state prediction using conditionally Gaussian observed Markov fuzzy switching model

Published:2022-05-25 Issue: Volume: Page:1-20
ISSN:1547-2450
Container-title:Journal of Intelligent Transportation Systems
language:en
Short-container-title:Journal of Intelligent Transportation Systems

Author:

Bouyahia Zied¹^ORCID,Haddad Hedi¹^ORCID,Derrode Stéphane²^ORCID,Pieczynski Wojciech³^ORCID

Affiliation:

1. College of Arts and Applied Sciences, Dhofar University, Salalah, Oman

2. Université de Lyon, CNRS, École Centrale de Lyon, LIRIS, CNRS UMR, Lyon, France

3. Institut Polytechnique de Paris, Telecom SudParis, SAMOVAR, Paris, France

Funder

The Research Council

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Information Systems,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15472450.2022.2069498

Reference60 articles.

1. Optimal Filter Approximations in Conditionally Gaussian Pairwise Markov Switching Models

2. Agudelo-España, D., Gomez-Gonzalez, S., Bauer, S., Schölkopf, B. & Peters, J. (2019). Bayesian online detection and prediction of change points. arXiv preprint arXiv:1902.04524.

3. A survey of methods for time series change point detection

4. Dynamic data-driven local traffic state estimation and prediction

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