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System risk importance analysis using bayesian networks

Noroozian, A ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1142/S0218539318500043
  3. Publisher: World Scientific Publishing Co. Pte Ltd , 2018
  4. Abstract:
  5. Importance measures (IMs) are used for risk-informed decision making in system operations, safety, and maintenance. Traditionally, they are computed within fault tree (FT) analysis. Although FT analysis is a powerful tool to study the reliability and structural characteristics of systems, Bayesian networks (BNs) have shown explicit advantages in modeling and analytical capabilities. In this paper, the traditional definitions of IMs are extended to BNs in order to have more capability in terms of system risk modeling and analysis. Implementation results on a case study illustrate the capability of finding the most important components in a system. © 2018 World Scientific Publishing Company
  6. Keywords:
  7. Bayesian networks ; Fault tree analysis ; Importance measures ; System risk ; Bayesian networks ; Decision making ; Knowledge based systems ; Reliability analysis ; Risk analysis ; Risk assessment ; Bayesian Networks (bns) ; Fault-trees ; Importance analysis ; Importance measure ; Risk-informed decision making ; Structural characteristics ; System operation ; System risk ; Fault tree analysis
  8. Source: International Journal of Reliability, Quality and Safety Engineering ; Volume 25, Issue 1 , 2018 ; 02185393 (ISSN)
  9. URL: https://www.worldscientific.com/doi/abs/10.1142/S0218539318500043