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Estimation of Bounds of the Set of Potential Number of Fuzzy Clusters in a Sought Clustering Structure

by Dmitri A. Viattchenin, Aliaksandr Yaroma, Aliaksandr Damaratski
journal cover thumbnail

Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 6 - Number 2
Year of Publication: 2016
Authors: Dmitri A. Viattchenin, Aliaksandr Yaroma, Aliaksandr Damaratski
10.5120/cae2016652089

Dmitri A. Viattchenin, Aliaksandr Yaroma, Aliaksandr Damaratski . Estimation of Bounds of the Set of Potential Number of Fuzzy Clusters in a Sought Clustering Structure. Communications on Applied Electronics. 6, 2 ( Nov 2016), 1-10. DOI=10.5120/cae2016652089

@article{ 10.5120/cae2016652089,
author = { Dmitri A. Viattchenin, Aliaksandr Yaroma, Aliaksandr Damaratski },
title = { Estimation of Bounds of the Set of Potential Number of Fuzzy Clusters in a Sought Clustering Structure },
journal = { Communications on Applied Electronics },
issue_date = { Nov 2016 },
volume = { 6 },
number = { 2 },
month = { Nov },
year = { 2016 },
issn = { 2394-4714 },
pages = { 1-10 },
numpages = {9},
url = { https://www.caeaccess.org/archives/volume6/number2/673-2016652089/ },
doi = { 10.5120/cae2016652089 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-09-04T19:56:04.996552+05:30
%A Dmitri A. Viattchenin
%A Aliaksandr Yaroma
%A Aliaksandr Damaratski
%T Estimation of Bounds of the Set of Potential Number of Fuzzy Clusters in a Sought Clustering Structure
%J Communications on Applied Electronics
%@ 2394-4714
%V 6
%N 2
%P 1-10
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, an approach to constructing the set of values of the most possible number of fuzzy clusters in a sought clustering structure is proposed. The proposed approach is based on heuristic possibilistic clustering and fuzzy numbers. For the purpose, fuzzy numbers are described and algorithms of the heuristic approach to possibilistic clustering are considered in brief. A procedure for constructing the set of values of the most possible number of fuzzy clusters is described for the object data set. An application of the proposed technique to the Anderson’s iris data set is provided and some concluding remarks are stated.

References
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  13. Viattchenin, D.A., Tati, R., and Damaratski, A.V. 2013. Designing Gaussian Membership Functions for Fuzzy Classifier Generated by Heuristic Possibilistic Clustering. Journal of Information and Organizational Sciences. 37, 2, 127-139.
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Index Terms

Computer Science
Information Sciences

Keywords

Triangular Fuzzy Number Gaussian Fuzzy Number Cluster Validity Heuristic Possibilistic Clustering Tolerance Threshold.

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