Cascading delays for the high-speed rail network under different emergencies: A double layer network approach-Reference-Cited by-同舟云学术

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Cascading delays for the high-speed rail network under different emergencies: A double layer network approach

Published:2022 Issue: Volume: Page:1-12
ISSN:2329-9266
Container-title:IEEE/CAA Journal of Automatica Sinica
language:
Short-container-title:IEEE/CAA J. Autom. Sinica

Author:

Wu Xingtang¹,Yang Mingkun²,Lian Wenbo²,Zhou Min²,Wang Hongwei³,Dong Hairong²

Affiliation:

1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China

2. State Key Laboratory of Rail Traffc Control and Safety, Beijing Jiaotong University, Beijing 100044, China

3. National Research Center of Railway Safety Assessment, Beijing Jiaotong University, Beijing 100044, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/6570654/7725587/09768787.pdf?arnumber=9768787

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1. Critical Spatial-Temporal Node Identification for a High-Speed Railway Network: A Cascading Delay Perspective;IEEE Transactions on Network Science and Engineering;2024-01

2. Hybrid Approach to Train Delay Prediction: An Integration of Analytical Model and Deep Learning Techniques;IEEE Transactions on Industrial Electronics;2024

3. Game Based Task Offloading in Cyber-Physical Systems for High-Speed Railway With Dynamic Latency and Energy Cost;IEEE Transactions on Industrial Cyber-Physical Systems;2024

4. Overview of fault prognosis for traction systems in high-speed trains: A deep learning perspective;Engineering Applications of Artificial Intelligence;2023-11

5. ACP-Based Parallel Railway Traffic Management for High-Speed Trains in Case of Emergencies;IEEE Transactions on Intelligent Vehicles;2023-11

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