A Parametric Exponential Entropy Measure for Neutrosophic Sets and It’s Application in Decision Making

In this paper, we propose a novel exponential entropy measure for Single-Valued Neutrosophic Sets. Neutrosophic sets as an extension of fuzzy and intuitionistic fuzzy sets, designed to handle uncertain, indeterminate, and inconsistent information in a more refined manner. The proposed entropy measure captures the degree of uncertainty inherent in single valued neutrosophic sets by simultaneously considering the truth-membership, indeterminacy-membership, and falsity-membership degrees. We establish the essential mathematical properties of the proposed entropy measure, including validation. Furthermore, illustrative examples and potential applications in decision-making is presented to validate the practical utility of the proposed measure.

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Publication Details

Journal
Statistics, Optimization & Information Computing (University of Cambridge)
Published
2026-02-24
DOI
https://doi.org/10.19139/soic-2310-5070-3129
Primary Topic
Multi-Criteria Decision Making
Type
article
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article

A Parametric Exponential Entropy Measure for Neutrosophic Sets and It’s Application in Decision Making

Vaishali M. Joshi, Sara Mohamed Ahmed Alsheikh, Javid Gani Dar
Statistics, Optimization & Information Computing (University of Cambridge)
Multi-Criteria Decision Making
article

A Parametric Exponential Entropy Measure for Neutrosophic Sets and It’s Application in Decision Making

Vaishali M. Joshi, Sara Mohamed Ahmed Alsheikh, Javid Gani Dar
article en

Abstract

In this paper, we propose a novel exponential entropy measure for Single-Valued Neutrosophic Sets. Neutrosophic sets as an extension of fuzzy and intuitionistic fuzzy sets, designed to handle uncertain, indeterminate, and inconsistent information in a more refined manner. The proposed entropy measure captures the degree of uncertainty inherent in single valued neutrosophic sets by simultaneously considering the truth-membership, indeterminacy-membership, and falsity-membership degrees. We establish the essential mathematical properties of the proposed entropy measure, including validation. Furthermore, illustrative examples and potential applications in decision-making is presented to validate the practical utility of the proposed measure.

Statistics, Optimization & Information Computing (University of Cambridge)
Peace, Justice and strong institutions
Openalex Percentile: Top 47%
Multi-Criteria Decision Making
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