Generalized Parametric Fuzzy Information Measure

Objective: To generalize an existing fuzzy information measure and verify its important properties. Methods: Both objective and descriptive methods have been adopted; problem-solving and problem-posing methods have been used. A collection of properties presented by De Luca and Termini is used as a standard for establishing new fuzzy information measures. Findings: This study has analysed the different features of the parametric measure of fuzzy information that we have presented. The suggested fuzzy entropy measure is a legitimate measure of fuzzy information since it meets all necessary requirements. Its monotonic behaviour has also been studied. Comparisons between the proposed measure of fuzzy information and the corresponding measure of probabilistic information have been discussed. Novelty: The unique quality of the suggested fuzzy information measure is found in its monotonic behaviour corresponding to parameter α. When conducting a multicriteria decision analysis and directing the decision-making process, monotonic fuzzy information measures are more useful. Because the suggested measure satisfies fundamental set features, it can be applied in soft computing for economics, decision-making, and data aggregation. Mathematics Subject Classification: 94 D 05 Keywords: Fuzzy Entropy, Uncertainty, Fuzziness, Measures of Information, Shannon Entropy