Title :
Reliability assessment under uncertainty using Dempster-Shafer and vague set theories
Author :
Pashazadeh, Saeid ; Sharifi, Mohsen
Author_Institution :
Dept. of Comput. Eng., Iran Univ. of Sci. & Technol., Tehran
Abstract :
Analyzing reliability of a system in design stage requires expertpsilas estimations and statistical data with various degrees of epistemic uncertainty and doing aggregation in a coherent framework. Dempster-Shafer (DS) theory is theorypotentially valuable tool for combination of evidence obtained from multiple different sources. One approach for fuzzy reliability assessment is using Vague set (VS) theory. DS theory has many similarities with VS theory. Uncertain raw data about the component reliability of a system can be combined using different combination methods of DS theory and can be represented in the form of triangular fuzzy vague number. Using the proper methods and equations, the fuzzy reliability of the system can be computed with triangular vague numbers of components reliability. Combining these two theories eliminates the gap between the representation of combined evidences and the way of representing the reliability of components in the VS theory for reliability assessment. Our proposed method eliminates this gap in very convenient form. Because of closed relevance of these two theories we can represent the output of DS combination in the form of vague triangular number in the VS theory. With this method we eliminate the loss of meaningful information in this conversion.
Keywords :
fuzzy set theory; nonmonotonic reasoning; number theory; reliability theory; statistical analysis; uncertainty handling; Dempster-Shafer theory; epistemic uncertainty; fuzzy component reliability assessment; statistical analysis; triangular fuzzy vague number; vague set theory; Fuzzy set theory; Fuzzy sets; Fuzzy systems; History; Performance analysis; Probability; Reliability engineering; Reliability theory; Set theory; Uncertainty; Dempster-Shafer theory; Fuzzy system reliability; Triangular fuzzy number; Uncertainty; Vague set theory;
Conference_Titel :
Computational Intelligence for Measurement Systems and Applications, 2008. CIMSA 2008. 2008 IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-2305-7
Electronic_ISBN :
978-1-4244-2306-4
DOI :
10.1109/CIMSA.2008.4595847