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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.23 No.3
- 발행연도
- 2023.9
- 수록면
- 318 - 335 (18page)
- DOI
- 10.5391/IJFIS.2023.23.3.318
이용수
초록· 키워드
오류제보하기
The parameters of lifetime distribution are frequently measured with some imprecision. However, classical lifetime analyses are based on precise measurement assumptions and cannot handle parameter imprecision. Accordingly, to accommodate the imprecision, the generalized intuitionistic fuzzy reliability analysis is preferred over classical reliability analysis. In reliability analysis, generalized intuitionistic fuzzy parameters provide a flexible model and elucidate the uncertainty and vagueness demanded in the reliability analysis. This study generalizes the parameters and reliability characteristics of the Moore and Bilikam family to cover the fuzziness of the lifetime parameters based on the generalized intuitionistic fuzzy numbers. The Moore and Bilikam family includes several lifetime distributions, such that the resulting reliability measures are more comprehensive than other lifetime distributions. The generalized intuitionistic fuzzy reliability functions and their α₁-cut and α₂-cut sets are provided, such as the reliability, conditional reliability, and hazard rate functions with generalized intuitionistic fuzzy parameters. We also evaluate the bands with upper and lower bounds in reliability measures than the curve. Based on a numerical example, the generalized intuitionistic fuzzy reliability measures are provided based on the Weibull distribution of the Moore and Bilikam family.
목차
Abstract
1. Introduction
2. Preliminaries
3. Generalized Intuitionistic Fuzzy Distribution
4. Reliability Characteristics
5. Numerical Example
6. Conclusion
References
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UCI(KEPA) : I410-ECN-0102-2023-003-002056136