1996
DOI: 10.1142/9789814261302_bmatter
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Cited by 20 publications
(31 citation statements)
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“…The set of non-fuzzy à and membership function μnormalA˜true(xtrue) is characterized by function Ã. The definition of fuzzy set → R is real numbers in fuzzy numbers (Klir and Yuan, 1995). The membership function provides the leverage of a set of quantitative assessments and notations Ã: R → [0,1].…”
Section: Methodsmentioning
confidence: 99%
“…The set of non-fuzzy à and membership function μnormalA˜true(xtrue) is characterized by function Ã. The definition of fuzzy set → R is real numbers in fuzzy numbers (Klir and Yuan, 1995). The membership function provides the leverage of a set of quantitative assessments and notations Ã: R → [0,1].…”
Section: Methodsmentioning
confidence: 99%
“…Lofti Zadeh introduced the idea of using fuzzy logic for systems control in 1972 (Klir & Yuan, 1995). This innovative way of considering possibilistic rather than probabilistic system performance outcomes improved the applicability of systems control methodology and design to practical “real-world” problems (Lewis, 1997).…”
Section: Antecedent Methodologiesmentioning
confidence: 99%
“…Step 2: Establishing triangular fuzzy numbers: calculate the evaluation value of the triangular fuzzy numbers of each candidate factor by experts to find the importance of the triangular fuzzy number of the candidate factor. In this study, the geometric mean proposed by Klir and Yuan (1995) is used as a method to calculate the consensus of group decision-making. The geometric mean represents the most likely value of this factor.…”
Section: Research Frameworkmentioning
confidence: 99%