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Fuzzy Measure Theory
Zhenyuan Wang,George J. Klir +1 more
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TLDR
Introduction.Abstract:
Introduction. Required Background in Set Theory. Fuzzy Measures. Extensions. Structural Characteristics for Set Functions. Measurable Functions on Fuzzy Measure Spaces. Fuzzy Integrals. PanIntegrals. Applications. Index.read more
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Book ChapterDOI
Several Applications Based on the Definite Integral Models for (Generalized) Intuitionistic (Multiplicative) Fuzzy Information
TL;DR: In this paper, the authors proposed a prepotent way to aggregate correlative data for decision making. But, since the data information collected may not be independent but associated, as well as their weight vector would also depend on the support level from the others, in this circumstance, other prepotent ways to aggregate data must be found.
Journal ArticleDOI
Fuzzy measures and generalized Möbius transform
TL;DR: By means of the generalized Möbius transform, a general concept of k -order additivity independent of the cardinality of the underlying space is introduced, and the relationship of the Choquet integral and the Lebesgue integral is clarified.
Journal ArticleDOI
A note on the null-additivity of the fuzzy measure: corrigendum to On the null-additivity of the fuzzy measure [Fuzzy Sets and Systems 78 (1996) 337-339]
TL;DR: In this article, the null-additivity of the fuzzy measure was shown to be not valid and a weaker condition was introduced to correct the results of Theorems 2 and 2' shown in the paper.
Proceedings ArticleDOI
Aggregation Functions as a Base for Decision Making
TL;DR: The paper presents the mathematical models based on aggregation functions for these uncertainties such as probability theory and statistics, and newer mathematical methods such as the theory of fuzzy sets and fuzzy logics, and nonadditive measures and integrals based on them.