Clustering Algorithm for Intuitionistic Fuzzy Graphs-Reference-Cited by-同舟云学术

Clustering Algorithm for Intuitionistic Fuzzy Graphs

Published:2017-05-22 Issue:03 Volume:25 Page:367-383
ISSN:0218-4885
Container-title:International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
language:en
Short-container-title:Int. J. Unc. Fuzz. Knowl. Based Syst.

Author:

Karunambigai M. G.¹,Akram Muhammad²,Sivasankar S.³,Palanivel K.⁴

Affiliation:

1. Department of Mathematics, Sri Vasavi College, Erode – 638 016, Tamilnadu, India

2. Department of Mathematics, University of Punjab, New campus, P.O. Box No. 54590, Lahore, Pakistan

3. Department of Science and Humanities, PES University, Bangalore-560085, Karnataka, India

4. Department of Mathematics, The Oxford College of Engineering, Bangalore-560068, Karnataka, India

Abstract

In this paper, we present certain algorithms for clustering the vertices of fuzzy graphs(FGs) and intuitionistic fuzzy graphs(IFGs). These algorithms are based on the edge density of the given graph. We apply the algorithms to practical problems to derive the most prominent cluster among them. We also introduce parameters for intuitionistic fuzzy graphs.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering,Software

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218488517500155

Reference19 articles.

1. Strong intuitionistic fuzzy graphs

2. Intuitionistic fuzzy hypergraphs with applications

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