Risk analysis in a linguistic environment: A fuzzy evidential reasoning-based approach

Yong Deng, Rehan Sadiq, Wen Jiang, Solomon Tesfamariam

Research output: Contribution to journalArticlepeer-review

128 Scopus citations

Abstract

Performing risk analysis can be a challenging task for complex systems due to lack of data and insufficient understanding of the failure mechanisms. A semi quantitative approach that can utilize imprecise information, uncertain data and domain experts' knowledge can be an effective way to perform risk analysis for complex systems. Though the definition of risk varies considerably across disciplines, it is a well accepted notion to use a composition of likelihood of system failure and the associated consequences (severity of loss). A complex system consists of various components, where these two elements of risk for each component can be linguistically described by the domain experts. The proposed linguistic approach is based on fuzzy set theory and Dempster-Shafer theory of evidence, where the later has been used to combine the risk of components to determine the system risk. The proposed risk analysis approach is demonstrated through a numerical example.

Original languageEnglish
Pages (from-to)15438-15446
Number of pages9
JournalExpert Systems with Applications
Volume38
Issue number12
DOIs
StatePublished - Nov 2011

Keywords

  • Complex systems
  • Dempster-Shafer theory of evidence
  • Fuzzy set theory
  • Risk analysis
  • Similarity measure

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