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Authors: Zhenhai Zhang ; Xiaozhen Yin and Zhilong Xu

Affiliation: School of Automation and Electrical Engineering, Lanzhou Jiaotong University, China

ISBN: 978-989-758-312-4

Keyword(s): railway transportation, emergency information, scenario deduction, event-driven model

Abstract: Railway emergency management is currently transforming from plan management to scenario management. Firstly, an event-driven model of scenario deduction for railway emergency was established. Then, according to the evolution process of scenarios for railway emergency, the emergency scenarios were divided into initial scenario, middle scenario and final scenario, among which the mutual relationships were analyzed. Furthermore, using Bayesian network inference algorithms, the specific process of scenario deduction for railway emergency was elaborated. Finally, taking train derailment accidentals for example, the states of node variables in scenario network were deduced. The scenario deduction results are in line with the real thing, which prove the proposed scheme feasible and effective.

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Paper citation in several formats:
Zhang, Z.; Yin, X. and Xu, Z. (2018). An Event-Driven Scheme of Scenario Deduction for Railway Emergency.In 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT, ISBN 978-989-758-312-4, pages 125-130. DOI: 10.5220/0006966201250130

@conference{icectt18,
author={Zhenhai Zhang. and Xiaozhen Yin. and Zhilong Xu.},
title={An Event-Driven Scheme of Scenario Deduction for Railway Emergency},
booktitle={3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,},
year={2018},
pages={125-130},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006966201250130},
isbn={978-989-758-312-4},
}

TY - CONF

JO - 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,
TI - An Event-Driven Scheme of Scenario Deduction for Railway Emergency
SN - 978-989-758-312-4
AU - Zhang, Z.
AU - Yin, X.
AU - Xu, Z.
PY - 2018
SP - 125
EP - 130
DO - 10.5220/0006966201250130

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