Research on the reliability model of emergency dispatch considering the advance state of time factor
- DOI
- 10.2991/978-94-6463-102-9_79How to use a DOI?
- Keywords
- System reliability; Emergency material dispatch; GO-Bayesian synthesis
- Abstract
With the frequent occurrence of major emergencies in recent years, the guarantee problem of emergency material dispatching has gradually come to the fore. In this paper, the reliability of the emergency material dispatching system is studied based on the analysis of the dispatching process and influencing factors, and the network model of system reliability is constructed by combining the GO method and Bayesian network as modelling tools. Bayesian forward and backward inference is used for fault inference to find out the system’s weak points. On this basis, the model is extended to the sensitivity study of system reliability. It is found that the material dispatching subsystem has the highest failure rate, in which material transportation time, emergency vehicle waiting time, implementation plan development time, satisfaction with the quantity of material at the affected point and agility of the dispatching information system are the main influencing factors.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jijun Xiao AU - Yutong Zhou AU - Shu Ou AU - Rong Kou PY - 2022 DA - 2022/12/29 TI - Research on the reliability model of emergency dispatch considering the advance state of time factor BT - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022) PB - Atlantis Press SP - 774 EP - 784 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-102-9_79 DO - 10.2991/978-94-6463-102-9_79 ID - Xiao2022 ER -