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Pattern Analysis and Applications
Erschienen in: Pattern Analysis and Applications 1/2016

01.02.2016 | Theoretical Advances

Entropy and similarity measure of Atanassov’s intuitionistic fuzzy sets and their application to pattern recognition based on fuzzy measures

verfasst von: Fanyong Meng, Xiaohong Chen

Erschienen in: Pattern Analysis and Applications | Ausgabe 1/2016

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Abstract

In this study, we first examine entropy and similarity measure of Atanassov’s intuitionistic fuzzy sets, and define a new entropy. Meanwhile, a construction approach to get the similarity measure of Atanassov’s intuitionistic fuzzy sets is introduced, which is based on entropy. Since the independence of elements in a set is usually violated, it is not suitable to aggregate the values for patterns by additive measures. Based on the given entropy and similarity measure, we study their application to Atanassov’s intuitionistic fuzzy pattern recognition problems under fuzzy measures, where the interactions between features are considered. To overall reflect the interactive characteristics between them, we define three Shapley-weighted similarity measures. Furthermore, if the information about the weights of features is incompletely known, models for the optimal fuzzy measure on feature set are established. Moreover, an approach to pattern recognition under Atanassov’s intuitionistic fuzzy environment is developed.
Vorheriger Artikel Tree-based binary image dissimilarity measure with meta-heuristic optimization
Nächster Artikel Histogram-based embedding for learning on statistical manifolds

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Metadaten
Titel
Entropy and similarity measure of Atanassov’s intuitionistic fuzzy sets and their application to pattern recognition based on fuzzy measures
verfasst von
Fanyong Meng
Xiaohong Chen
Publikationsdatum
01.02.2016
Verlag
Springer London
Erschienen in
Pattern Analysis and Applications / Ausgabe 1/2016
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI
https://doi.org/10.1007/s10044-014-0378-6

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