Cargando…

Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems

Many problems of practical interest can be modeled and solved by using graph algorithms. In general, graph theory has a wide range of applications in diverse fields. In this paper, the intuitionistic fuzzy organizational and neural network models, intuitionistic fuzzy neurons in medical diagnosis, i...

Descripción completa

Detalles Bibliográficos
Autores principales: Akram, Muhammad, Ashraf, Ather, Sarwar, Mansoor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4083274/
https://www.ncbi.nlm.nih.gov/pubmed/25045752
http://dx.doi.org/10.1155/2014/904606
_version_ 1782324350836277248
author Akram, Muhammad
Ashraf, Ather
Sarwar, Mansoor
author_facet Akram, Muhammad
Ashraf, Ather
Sarwar, Mansoor
author_sort Akram, Muhammad
collection PubMed
description Many problems of practical interest can be modeled and solved by using graph algorithms. In general, graph theory has a wide range of applications in diverse fields. In this paper, the intuitionistic fuzzy organizational and neural network models, intuitionistic fuzzy neurons in medical diagnosis, intuitionistic fuzzy digraphs in vulnerability assessment of gas pipeline networks, and intuitionistic fuzzy digraphs in travel time are presented as examples of intuitionistic fuzzy digraphs in decision support system. We have also designed and implemented the algorithms for these decision support systems.
format Online
Article
Text
id pubmed-4083274
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Hindawi Publishing Corporation
record_format MEDLINE/PubMed
spelling pubmed-40832742014-07-20 Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems Akram, Muhammad Ashraf, Ather Sarwar, Mansoor ScientificWorldJournal Research Article Many problems of practical interest can be modeled and solved by using graph algorithms. In general, graph theory has a wide range of applications in diverse fields. In this paper, the intuitionistic fuzzy organizational and neural network models, intuitionistic fuzzy neurons in medical diagnosis, intuitionistic fuzzy digraphs in vulnerability assessment of gas pipeline networks, and intuitionistic fuzzy digraphs in travel time are presented as examples of intuitionistic fuzzy digraphs in decision support system. We have also designed and implemented the algorithms for these decision support systems. Hindawi Publishing Corporation 2014 2014-06-16 /pmc/articles/PMC4083274/ /pubmed/25045752 http://dx.doi.org/10.1155/2014/904606 Text en Copyright © 2014 Muhammad Akram et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Akram, Muhammad
Ashraf, Ather
Sarwar, Mansoor
Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems
title Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems
title_full Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems
title_fullStr Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems
title_full_unstemmed Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems
title_short Novel Applications of Intuitionistic Fuzzy Digraphs in Decision Support Systems
title_sort novel applications of intuitionistic fuzzy digraphs in decision support systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4083274/
https://www.ncbi.nlm.nih.gov/pubmed/25045752
http://dx.doi.org/10.1155/2014/904606
work_keys_str_mv AT akrammuhammad novelapplicationsofintuitionisticfuzzydigraphsindecisionsupportsystems
AT ashrafather novelapplicationsofintuitionisticfuzzydigraphsindecisionsupportsystems
AT sarwarmansoor novelapplicationsofintuitionisticfuzzydigraphsindecisionsupportsystems