Identification of Fuzzy Measures with Distorted Probability Measures

We consider the identification of fuzzy measures using a class of distorted probabilities – a scale transformation of probabilities. A fuzzy measure, which is a nonadditive set function with a high degree of freedom, enables us to express complicated interactions among evaluative items. Because of t...

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Bibliographic Details
Published in:Journal of advanced computational intelligence and intelligent informatics Vol. 9; no. 5; pp. 467 - 476
Main Authors: Honda, Aoi, Okazaki, Yoshiaki
Format: Journal Article
Language:English
Published: 01.09.2005
ISSN:1343-0130, 1883-8014
Online Access:Get full text
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Summary:We consider the identification of fuzzy measures using a class of distorted probabilities – a scale transformation of probabilities. A fuzzy measure, which is a nonadditive set function with a high degree of freedom, enables us to express complicated interactions among evaluative items. Because of the high degree of freedom, however, it is difficult to identify all of the values μ(A) for every event A from known data μ(B), B ∈ A , where A is generally a small subclass of events. In this paper, we classify fuzzy measures by introducing “type,” and propose an identifying fuzzy measures using a classified class of distorted probabilities.
ISSN:1343-0130
1883-8014
DOI:10.20965/jaciii.2005.p0467