A predictive model of train delays on a railway line
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DOI: 10.1002/for.2639
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References listed on IDEAS
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- Sobrie, Léon & Verschelde, Marijn & Hennebel, Veerle & Roets, Bart, 2023. "Capturing complexity over space and time via deep learning: An application to real-time delay prediction in railways," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1201-1217.
- Tiong, Kah Yong & Ma, Zhenliang & Palmqvist, Carl-William, 2023. "Analyzing factors contributing to real-time train arrival delays using seemingly unrelated regression models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
- Luo, Jie & Wen, Chao & Peng, Qiyuan & Qin, Yong & Huang, Ping, 2023. "Forecasting the effect of traffic control strategies in railway systems: A hybrid machine learning method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
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