Markov-Based Time Series Modeling Framework for Traffic-Network State Prediction under Various External Conditions-Reference-Cited by-同舟云学术

Markov-Based Time Series Modeling Framework for Traffic-Network State Prediction under Various External Conditions

Published:2020-06 Issue:6 Volume:146 Page:04020042
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Li Tao¹,Ma Jiaqi²,Lee Changju³^ORCID

Affiliation:

1. Graduate Research Assistant, Dept. of Civil and Architectural Engineering and Construction Management, Univ. of Cincinnati, 765 Baldwin Hall, Cincinnati, OH 45221.

2. Assistant Professor, Dept. of Civil and Architectural Engineering and Construction Management, Univ. of Cincinnati, 765 Baldwin Hall, Cincinnati, OH 45221 (corresponding author).

3. Research Associate, Virginia Transportation Research Council, 530 Edgemont Rd., Charlottesville, VA 22903. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/JTEPBS.0000347

Reference14 articles.

1. Traffic Prediction Using Multivariate Nonparametric Regression

2. The Ensemble Kalman Filter: theoretical formulation and practical implementation

3. Optimizing Traffic Prediction Performance of Neural Networks under Various Topological, Input, and Traffic Condition Settings

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