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International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 2/2019

07.09.2017 | Original Article

Some distances, similarity and entropy measures for interval-valued neutrosophic sets and their relationship

verfasst von: Jun Ye, Shigui Du

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 2/2019

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Abstract

This paper proposes some new distance measures between interval-valued neutrosophic sets (IvNSs) and their similarity measures. Then, some entropy measures of IvNS based on the distances are proposed as the extension of the entropy measures of interval-valued intuitionistic fuzzy sets (IvIFSs). Also, we investigate the relationship between the presented entropy measures and the similarity measures for IvNSs. Finally, the comparison of the new entropy measures with existing entropy measures for IvNSs is given by the numerical and decision-making examples to demonstrate that the proposed new entropy measures for IvNSs are effective and reasonable and more intelligible in representing the degree of fuzziness of IvNSs than the existing ones.
Vorheriger Artikel N-semble: neural network based ensemble approach
Nächster Artikel KNN-based maximum margin and minimum volume hyper-sphere machine for imbalanced data classification

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Metadaten
Titel
Some distances, similarity and entropy measures for interval-valued neutrosophic sets and their relationship
verfasst von
Jun Ye
Shigui Du
Publikationsdatum
07.09.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 2/2019
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-017-0719-z

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