Interval Valued Intuitionistic Fuzzy Gaussian Membership Function: A Novel Extension

The Interval-valued intuitionistic fuzzy sets (IVIFSs) have long been used to model vagueness and have been used in decision making, pattern recognition, image processing, and other applications. In this study, IVIFSs are defined using Gaussian membership functions (GMFs), and new measures of the di...

Descripción completa

Detalles Bibliográficos
Autor principal: Bharatraj, Janani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351572/
http://dx.doi.org/10.1007/978-3-030-51156-2_44
_version_ 1783557466962788352
author Bharatraj, Janani
author_facet Bharatraj, Janani
author_sort Bharatraj, Janani
collection PubMed
description The Interval-valued intuitionistic fuzzy sets (IVIFSs) have long been used to model vagueness and have been used in decision making, pattern recognition, image processing, and other applications. In this study, IVIFSs are defined using Gaussian membership functions (GMFs), and new measures of the distance, the overlap, and the angle between two sets are developed. The proposed methodology is used to determine the similarities between test subjects in genetic brain profiling.
format Online
Article
Text
id pubmed-7351572
institution National Center for Biotechnology Information
language English
publishDate 2020
record_format MEDLINE/PubMed
spelling pubmed-73515722020-07-13 Interval Valued Intuitionistic Fuzzy Gaussian Membership Function: A Novel Extension Bharatraj, Janani Intelligent and Fuzzy Techniques: Smart and Innovative Solutions Article The Interval-valued intuitionistic fuzzy sets (IVIFSs) have long been used to model vagueness and have been used in decision making, pattern recognition, image processing, and other applications. In this study, IVIFSs are defined using Gaussian membership functions (GMFs), and new measures of the distance, the overlap, and the angle between two sets are developed. The proposed methodology is used to determine the similarities between test subjects in genetic brain profiling. 2020-06-10 /pmc/articles/PMC7351572/ http://dx.doi.org/10.1007/978-3-030-51156-2_44 Text en © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 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
Bharatraj, Janani
Interval Valued Intuitionistic Fuzzy Gaussian Membership Function: A Novel Extension
title Interval Valued Intuitionistic Fuzzy Gaussian Membership Function: A Novel Extension
title_full Interval Valued Intuitionistic Fuzzy Gaussian Membership Function: A Novel Extension
title_fullStr Interval Valued Intuitionistic Fuzzy Gaussian Membership Function: A Novel Extension
title_full_unstemmed Interval Valued Intuitionistic Fuzzy Gaussian Membership Function: A Novel Extension
title_short Interval Valued Intuitionistic Fuzzy Gaussian Membership Function: A Novel Extension
title_sort interval valued intuitionistic fuzzy gaussian membership function: a novel extension
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351572/
http://dx.doi.org/10.1007/978-3-030-51156-2_44
work_keys_str_mv AT bharatrajjanani intervalvaluedintuitionisticfuzzygaussianmembershipfunctionanovelextension

Ejemplares similares