Physics Guided Deep Learning-Based Model for Short-Term Origin–Destination Demand Prediction in Urban Rail Transit Systems Under Pandemic

Physics Guided Deep Learning-Based Model for Short-Term Origin–Destination Demand Prediction in Urban Rail Transit Systems Under Pandemic

Accurate origin–destination (OD) demand prediction is crucial for the efficient operation and management of urban rail transit (URT) systems, particularly during a pandemic. However, this task faces several limitations, including real-time availability, sparsity, and high-dimensionality issues, and...

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Bibliographic Details
Main Authors: Shuxin Zhang, Jinlei Zhang, Lixing Yang, Feng Chen, Shukai Li, Ziyou Gao
Format: Article
Language:English
Published: Elsevier 2024-10-01
Series:Engineering
Subjects:
Short–term origin–destination demand prediction
Urban rail transit
Pandemic
Physics-guided deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2095809924002637

Internet

http://www.sciencedirect.com/science/article/pii/S2095809924002637

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