Redefining fuzzy entropy with a general framework. (February 2021)

• Record Type: Journal Article
• Authors: Aggarwal, Manish
• Is Part Of: Expert systems with applications. Volume 164(2021)
• Publication Date: 2021-02
• Subjects: Fuzzy entropy -- Uncertainty -- Decision-making -- Subjective uncertainty -- Probabilistic-fuzzy; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2020.113671
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Ambiguity over membership grade as a natural uncertainty indicator. Different fuzzy entropy functions with different range of values. Fuzzy entropy and the difficulty to distinguish membership from non-membership. Uniformity between the forms of fuzzy and probabilistic entropy functions. Combination of fuzzy and probabilistic uncertainties. Abstract: A general entropy framework is proposed, which could lead to intuitive, interpretable and comparable entropy functions in both probabilistic or fuzzy domain, alike. Based on the proposed general entropy framework, the existing fuzzy entropy functions are redefined. The proposed entropy functions are also extended to the probabilistic-fuzzy domain. The usefulness of the work is shown in a real world case-study.