A Heuristic Approach to Possibilistic Clustering for Fuzzy Data

<span style="font-family: TimesNewRomanPSMT; font-size: x-small;"><span style="font-family: TimesNewRomanPSMT; font-size: x-small;"><p align="left">The paper deals with the problem of the fuzzy data clustering. In other words, objects attributes can be...

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Main Author: Dmitri A. Viattchenin
Format: Article
Language:English
Published: University of Zagreb, Faculty of organization and informatics 2008-12-01
Series:Journal of Information and Organizational Sciences
Subjects:
Online Access:http://jios.foi.hr/index.php/jios/article/view/74
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author Dmitri A. Viattchenin
author_facet Dmitri A. Viattchenin
author_sort Dmitri A. Viattchenin
collection DOAJ
description <span style="font-family: TimesNewRomanPSMT; font-size: x-small;"><span style="font-family: TimesNewRomanPSMT; font-size: x-small;"><p align="left">The paper deals with the problem of the fuzzy data clustering. In other words, objects attributes can be represented by fuzzy numbers or fuzzy intervals. A direct algorithm of possibilistic clustering is the basis of an approach to the fuzzy data clustering. The paper provides the basic ideas of the method of clustering and a plan of the direct possibilistic clustering algorithm. Definitions of fuzzy intervals and fuzzy numbers are presented and distances for fuzzy numbers are considered. A concept of a vector of fuzzy numbers is introduced and the fuzzy data preprocessing methodology for constructing of a fuzzy tolerance matrix is described. A numerical example is given and results of application of the direct possibilistic clustering algorithm to a set of vectors of triangular fuzzy numbers are considered in the example. Some preliminary conclusions are stated.</p></span></span>
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spelling doaj.art-358196a98d11426ba59f8b10f62372472022-12-21T21:34:47ZengUniversity of Zagreb, Faculty of organization and informaticsJournal of Information and Organizational Sciences1846-33121846-94182008-12-0132253A Heuristic Approach to Possibilistic Clustering for Fuzzy DataDmitri A. Viattchenin0Senior Researcher<span style="font-family: TimesNewRomanPSMT; font-size: x-small;"><span style="font-family: TimesNewRomanPSMT; font-size: x-small;"><p align="left">The paper deals with the problem of the fuzzy data clustering. In other words, objects attributes can be represented by fuzzy numbers or fuzzy intervals. A direct algorithm of possibilistic clustering is the basis of an approach to the fuzzy data clustering. The paper provides the basic ideas of the method of clustering and a plan of the direct possibilistic clustering algorithm. Definitions of fuzzy intervals and fuzzy numbers are presented and distances for fuzzy numbers are considered. A concept of a vector of fuzzy numbers is introduced and the fuzzy data preprocessing methodology for constructing of a fuzzy tolerance matrix is described. A numerical example is given and results of application of the direct possibilistic clustering algorithm to a set of vectors of triangular fuzzy numbers are considered in the example. Some preliminary conclusions are stated.</p></span></span>http://jios.foi.hr/index.php/jios/article/view/74possibilistic clusteringfuzzy toleranceallotment among fuzzy clusterstypical pointvector of fuzzy numbers
spellingShingle Dmitri A. Viattchenin
A Heuristic Approach to Possibilistic Clustering for Fuzzy Data
Journal of Information and Organizational Sciences
possibilistic clustering
fuzzy tolerance
allotment among fuzzy clusters
typical point
vector of fuzzy numbers
title A Heuristic Approach to Possibilistic Clustering for Fuzzy Data
title_full A Heuristic Approach to Possibilistic Clustering for Fuzzy Data
title_fullStr A Heuristic Approach to Possibilistic Clustering for Fuzzy Data
title_full_unstemmed A Heuristic Approach to Possibilistic Clustering for Fuzzy Data
title_short A Heuristic Approach to Possibilistic Clustering for Fuzzy Data
title_sort heuristic approach to possibilistic clustering for fuzzy data
topic possibilistic clustering
fuzzy tolerance
allotment among fuzzy clusters
typical point
vector of fuzzy numbers
url http://jios.foi.hr/index.php/jios/article/view/74
work_keys_str_mv AT dmitriaviattchenin aheuristicapproachtopossibilisticclusteringforfuzzydata
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