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

  • Authors:

  • Yong Deng;Rehan Sadiq;Wen Jiang;Solomon Tesfamariam

  • Affiliations:

  • College of Computer and Information Sciences, Southwest University, Chongqing 400715, China;Okanagan School of Engineering, University of British Columbia, Kelowna, BC, Canada;School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China;Okanagan School of Engineering, University of British Columbia, Kelowna, BC, Canada

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

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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.