NORMALIZATION, INACCURACY AND CRISPNESS

The conception of distance is pertinent to practically every field of Engineering and Science from a block of brick to a chromosome, which encourages en-route forth expansion of numerous mathematical models. It is usual that the conception can be protracted to contributions in further disciplines as...

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Published inAdvances and applications in mathematical sciences Vol. 18; no. 1; pp. 1 - 14
Main Authors Buttar, G S, Singh, Vikramjeet, Kaur, Harpreet
Format Journal Article
LanguageEnglish
Published Allahabad Mili Publications 01.11.2018
Subjects
Divergence
Entropy
Fuzzy sets
Mathematical models
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ISSN0974-6803

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Summary:The conception of distance is pertinent to practically every field of Engineering and Science from a block of brick to a chromosome, which encourages en-route forth expansion of numerous mathematical models. It is usual that the conception can be protracted to contributions in further disciplines as well. In this communication, expressions for the normalized measures of divergence for fuzzy distributions are derived as normalized measures are more convenient for comparison, relation between the fuzzy entropy, divergence and inaccuracy between two fuzzy sets is obtained.
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ISSN:0974-6803