A Knowledge Transfer-based Methodology for Risk Assessment of Emergency Schemes

Xu An, Huixing Meng*, Xuan Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Due to insufficient knowledge of rare accidents, it is essential to transfer knowledge from source systems with sufficient cases into target systems with limited cases. In this study, a knowledge transfer-based methodology is proposed to evaluate emergency schemes from the perspective of emergency risk in presence of limited accident cases. By considering dynamic evolution and operational characteristics of accidents, a hybrid model integrating dynamic Bayesian networks (DBN) and program evaluation and review technique (PERT) is introduced. In the integrated model, we transferred graph structures and parameters to obtain emergency schemes based on the similarities between the source systems and target systems. On the one hand, to design the operation of emergency schemes, we utilized PERT to judge the logical relationships and the response-time requirement of the emergency procedures. On the other hand, to evaluate and prevent emergency risk, we employed DBN to conduct the dynamic risk assessment of emergency operations.

Original languageEnglish
Title of host publication2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022
EditorsWei Guo, Steven Li
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665496315
DOIs
Publication statusPublished - 2022
Event2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022 - Yantai, China
Duration: 13 Oct 202216 Oct 2022

Publication series

Name2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022

Conference

Conference2022 Global Reliability and Prognostics and Health Management Conference, PHM-Yantai 2022
Country/TerritoryChina
CityYantai
Period13/10/2216/10/22

Keywords

  • DBN
  • Keywords-emergency scheme
  • PERT
  • knowledge transfer

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