Open AccessBook
Fuzzy Measure Theory
Zhenyuan Wang,George J. Klir +1 more
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
Citations
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Journal ArticleDOI
Consensus dynamics, network interaction, and Shapley indices in the Choquet framework
TL;DR: Two types of consensus dynamics are discussed, both of which refer significantly to the notion of context opinion, and the second type converges simply the plain mean, whereas the first type produces the Shapley mean as the asymptotic consensual opinion.
Proceedings ArticleDOI
Using generalized Choquet integral in projection pursuit based classification
TL;DR: A generalized Choquet integral with respect to a nonadditive sign measure is proposed, and serves as an aggregation tool to project the points of feature space onto a real axis to reduce an n-dimensional classification problem into a one- dimensional classification problem.
Proceedings ArticleDOI
An intelligent system in healthcare using fuzzy measures
A.S. Wagholikar,Jun Jo +1 more
TL;DR: This work proposes an approach to resolve issues associated with practical implementation of fuzzy measures using similarity-based reasoning and demonstrates the suitability of fuzzy Measures in critical health care systems.
Journal ArticleDOI
Option Pricing Model with Fuzzy Measures under Knightian Uncertainty
Li-yan Han,Juan Zhou +1 more
TL;DR: In this article, an option-pricing model is proposed under Knightian uncertainty using the λ-fuzzy measure and the Choquet integral, and the equilibrium price of European option on a non-dividend-paying stock is deduced.
Proceedings Article
A multiperiod binomial model for pricing options in an uncertain world
TL;DR: This paper provides a generalization of the standard binomial option pricing model and obtains an expected value interval for the option price within which it is possible to find a crisp representative value and an index of the uncertainty present in the model.