직관 퍼지 와이블 분포에서 알파 컷 셋을 이용한시스템 신뢰성 분석System Reliability Analysis Using α-Cut Set in Intuitionistic Fuzzy Weibull Distribution
- Other Titles
- System Reliability Analysis Using α-Cut Set in Intuitionistic Fuzzy Weibull Distribution
- Authors
- 최성운
- Issue Date
- Sep-2021
- Publisher
- 한국경영공학회
- Keywords
- IFS; α-Cut Set; Weibull; System Reliability; Uncertainty Types; Belief; Disbelief; Unbelief
- Citation
- 한국경영공학회지, v.26, no.3, pp.23 - 46
- Journal Title
- 한국경영공학회지
- Volume
- 26
- Number
- 3
- Start Page
- 23
- End Page
- 46
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/82261
- DOI
- 10.35373/KMES.26.3.2
- ISSN
- 2005-7776
- Abstract
- (Purpose) This study is to analyze system reliability using fuzzy Weibull lifetime distribution in which scale parameters are assumed to be Intuitionistic Fuzzy Set (IFS) with α-cut set due to uncertainties and inaccuracy of data.
(Methods) The IFS is utilized to present the information of membership function and non-membership function with the three intervals that include belief, disbelief and unbelief functions. The paper discusses the intuitionistic fuzzy Weibull system reliability models to assess the membership function and non-membership function by considering the different types of component intuitionistic fuzzy scale parameter. Due to the existence of different types of uncertainties, the three types of component TIFS (Triangular IFS) and TrIFS (Trapezoidal IFS) with α-cut set were presented for computing intuitionistic fuzzy system reliability in both series structure and parallel structure.
(Results) The validity of proposed model is demonstrated by analyzing intuitionistic fuzzy Weibull system reliabilities with α-cut set using different types of intuitionistic fuzzy scale parameter. A numerical example is indicated to discuss the usefulness and practicality of the proposed model.
(Conclusions) When conducting a group decision making for evaluating the intuitionistic fuzzy Weibull system reliability, α-cut set models proposed in this paper can be used to reflect various experts’ judgments on agreement, disagreement and undecidedness when evaluating system reliability.
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