Sequence of inequalities among fuzzy mean difference divergence measures and their applications

This paper presents a sequence of fuzzy mean difference divergence measures. The validity of these fuzzy mean difference divergence measures is proved axiomatically. In addition, it introduces a sequence of inequalities among some of these fuzzy mean difference divergence measures. The applications...

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Detalles Bibliográficos
Autores principales: Tomar, Vijay Prakash, Ohlan, Anshu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2014
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4216826/
https://www.ncbi.nlm.nih.gov/pubmed/25392793
http://dx.doi.org/10.1186/2193-1801-3-623
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author Tomar, Vijay Prakash
Ohlan, Anshu
author_facet Tomar, Vijay Prakash
Ohlan, Anshu
author_sort Tomar, Vijay Prakash
collection PubMed
description This paper presents a sequence of fuzzy mean difference divergence measures. The validity of these fuzzy mean difference divergence measures is proved axiomatically. In addition, it introduces a sequence of inequalities among some of these fuzzy mean difference divergence measures. The applications of proposed fuzzy mean difference divergence measures in the context of pattern recognition have been presented using a numerical example. It is shown that the proposed fuzzy mean difference divergence measures are well suited to use with linguistic variables. Finally, on establishing inequalities, we find that our proposed measures are computationally much more efficient.
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spelling pubmed-42168262014-11-12 Sequence of inequalities among fuzzy mean difference divergence measures and their applications Tomar, Vijay Prakash Ohlan, Anshu Springerplus Research This paper presents a sequence of fuzzy mean difference divergence measures. The validity of these fuzzy mean difference divergence measures is proved axiomatically. In addition, it introduces a sequence of inequalities among some of these fuzzy mean difference divergence measures. The applications of proposed fuzzy mean difference divergence measures in the context of pattern recognition have been presented using a numerical example. It is shown that the proposed fuzzy mean difference divergence measures are well suited to use with linguistic variables. Finally, on establishing inequalities, we find that our proposed measures are computationally much more efficient. Springer International Publishing 2014-10-22 /pmc/articles/PMC4216826/ /pubmed/25392793 http://dx.doi.org/10.1186/2193-1801-3-623 Text en © Tomar and Ohlan; licensee Springer. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Research
Tomar, Vijay Prakash
Ohlan, Anshu
Sequence of inequalities among fuzzy mean difference divergence measures and their applications
title Sequence of inequalities among fuzzy mean difference divergence measures and their applications
title_full Sequence of inequalities among fuzzy mean difference divergence measures and their applications
title_fullStr Sequence of inequalities among fuzzy mean difference divergence measures and their applications
title_full_unstemmed Sequence of inequalities among fuzzy mean difference divergence measures and their applications
title_short Sequence of inequalities among fuzzy mean difference divergence measures and their applications
title_sort sequence of inequalities among fuzzy mean difference divergence measures and their applications
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4216826/
https://www.ncbi.nlm.nih.gov/pubmed/25392793
http://dx.doi.org/10.1186/2193-1801-3-623
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