Capturing complexity over space and time via deep learning : an application to real-time delay prediction in railways
- Author
- Léon Sobrie (UGent) , Marijn Verschelde (UGent) , Veerle Hennebel and Bart Roets (UGent)
- Organization
- Keywords
- Information Systems and Management, Management Science and Operations Research, Modeling and Simulation, General Computer Science, Industrial and Manufacturing Engineering, Analytics, Deep learning, Railway transportation, Delays, Complexity, NEURAL-NETWORKS, BIG DATA, ANALYTICS, WORKLOAD, SYSTEMS
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01H396662Q0ASTJMW0WHZ8JV92
- MLA
- Sobrie, Léon, et al. “Capturing Complexity over Space and Time via Deep Learning : An Application to Real-Time Delay Prediction in Railways.” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol. 310, no. 3, 2023, pp. 1201–17, doi:10.1016/j.ejor.2023.03.040.
- APA
- Sobrie, L., Verschelde, M., Hennebel, V., & Roets, B. (2023). Capturing complexity over space and time via deep learning : an application to real-time delay prediction in railways. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 310(3), 1201–1217. https://doi.org/10.1016/j.ejor.2023.03.040
- Chicago author-date
- Sobrie, Léon, Marijn Verschelde, Veerle Hennebel, and Bart Roets. 2023. “Capturing Complexity over Space and Time via Deep Learning : An Application to Real-Time Delay Prediction in Railways.” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 310 (3): 1201–17. https://doi.org/10.1016/j.ejor.2023.03.040.
- Chicago author-date (all authors)
- Sobrie, Léon, Marijn Verschelde, Veerle Hennebel, and Bart Roets. 2023. “Capturing Complexity over Space and Time via Deep Learning : An Application to Real-Time Delay Prediction in Railways.” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 310 (3): 1201–1217. doi:10.1016/j.ejor.2023.03.040.
- Vancouver
- 1.Sobrie L, Verschelde M, Hennebel V, Roets B. Capturing complexity over space and time via deep learning : an application to real-time delay prediction in railways. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH. 2023;310(3):1201–17.
- IEEE
- [1]L. Sobrie, M. Verschelde, V. Hennebel, and B. Roets, “Capturing complexity over space and time via deep learning : an application to real-time delay prediction in railways,” EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, vol. 310, no. 3, pp. 1201–1217, 2023.
@article{01H396662Q0ASTJMW0WHZ8JV92,
author = {{Sobrie, Léon and Verschelde, Marijn and Hennebel, Veerle and Roets, Bart}},
issn = {{0377-2217}},
journal = {{EUROPEAN JOURNAL OF OPERATIONAL RESEARCH}},
keywords = {{Information Systems and Management,Management Science and Operations Research,Modeling and Simulation,General Computer Science,Industrial and Manufacturing Engineering,Analytics,Deep learning,Railway transportation,Delays,Complexity,NEURAL-NETWORKS,BIG DATA,ANALYTICS,WORKLOAD,SYSTEMS}},
language = {{eng}},
number = {{3}},
pages = {{1201--1217}},
title = {{Capturing complexity over space and time via deep learning : an application to real-time delay prediction in railways}},
url = {{http://doi.org/10.1016/j.ejor.2023.03.040}},
volume = {{310}},
year = {{2023}},
}
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