期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 38, 期 12, 页码 15438-15446出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2011.06.018
关键词
Risk analysis; Complex systems; Dempster-Shafer theory of evidence; Fuzzy set theory; Similarity measure
类别
资金
- Canada NSERC
- National Natural Science Foundation of China [60874105]
- Program for New Century Excellent Talents in University [NCET-08-0345]
- Shanghai Rising-Star Program [09QA1402900]
- Chongqing Natural Science Foundation [CSCT, 2010BA2003]
- Fundamental Research Funds for the Central Universities [XDJK2010C030]
- Shanghai Jiao Tong University [T241460612]
- National Defence Sciences Funding of Shanghai Jiao Tong University [11GFF-17]
- Southwest University [SWU110021]
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. (C) 2011 Elsevier Ltd. All rights reserved.
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