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An Initial Study on Typical Hesitant (T,N)-Implication Functions

In the theory of Hesitant Fuzzy Sets (HFS), the membership degree of an element is characterized by a membership function which always returns a fuzzy set. This approach enables one to express, for example, the hesitance of several experts in the process of decision making based on multiple attribut...

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Autores principales: Matzenauer, Monica, Reiser, Renata, Santos, Helida, Pinheiro, Jocivania, Bedregal, Benjamin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274708/
http://dx.doi.org/10.1007/978-3-030-50143-3_58
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author Matzenauer, Monica
Reiser, Renata
Santos, Helida
Pinheiro, Jocivania
Bedregal, Benjamin
author_facet Matzenauer, Monica
Reiser, Renata
Santos, Helida
Pinheiro, Jocivania
Bedregal, Benjamin
author_sort Matzenauer, Monica
collection PubMed
description In the theory of Hesitant Fuzzy Sets (HFS), the membership degree of an element is characterized by a membership function which always returns a fuzzy set. This approach enables one to express, for example, the hesitance of several experts in the process of decision making based on multiple attributes and multiple criteria. In this work, we focus on the study of a class of implication functions for typical hesitant fuzzy sets (THFS). The novelty of our proposal lies on the fact that it is the first time that an admissible order is used to define operators on hesitant fuzzy setting. Thus, we introduce typical hesitant fuzzy negations, typical hesitant t-norms and typical hesitant implication functions considering an admissible order, which allows the comparison of typical hesitant fuzzy elements with different cardinalities.
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spelling pubmed-72747082020-06-08 An Initial Study on Typical Hesitant (T,N)-Implication Functions Matzenauer, Monica Reiser, Renata Santos, Helida Pinheiro, Jocivania Bedregal, Benjamin Information Processing and Management of Uncertainty in Knowledge-Based Systems Article In the theory of Hesitant Fuzzy Sets (HFS), the membership degree of an element is characterized by a membership function which always returns a fuzzy set. This approach enables one to express, for example, the hesitance of several experts in the process of decision making based on multiple attributes and multiple criteria. In this work, we focus on the study of a class of implication functions for typical hesitant fuzzy sets (THFS). The novelty of our proposal lies on the fact that it is the first time that an admissible order is used to define operators on hesitant fuzzy setting. Thus, we introduce typical hesitant fuzzy negations, typical hesitant t-norms and typical hesitant implication functions considering an admissible order, which allows the comparison of typical hesitant fuzzy elements with different cardinalities. 2020-05-15 /pmc/articles/PMC7274708/ http://dx.doi.org/10.1007/978-3-030-50143-3_58 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Matzenauer, Monica
Reiser, Renata
Santos, Helida
Pinheiro, Jocivania
Bedregal, Benjamin
An Initial Study on Typical Hesitant (T,N)-Implication Functions
title An Initial Study on Typical Hesitant (T,N)-Implication Functions
title_full An Initial Study on Typical Hesitant (T,N)-Implication Functions
title_fullStr An Initial Study on Typical Hesitant (T,N)-Implication Functions
title_full_unstemmed An Initial Study on Typical Hesitant (T,N)-Implication Functions
title_short An Initial Study on Typical Hesitant (T,N)-Implication Functions
title_sort initial study on typical hesitant (t,n)-implication functions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274708/
http://dx.doi.org/10.1007/978-3-030-50143-3_58
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