Analysis of similarity coefficients in fuzzy node fuzzy graph and its application

Hiroaki Uesu, Shuya Kanagawa, Kimiaki Shinkai, Kenichi Nagashima

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Generally, we could efficiently analyze the inexact information and investigate the fuzzy relation by applying the fuzzy graph theory. We would extend the fuzzy graph theory, and propose a fuzzy node fuzzy graph. Since a fuzzy node fuzzy graph is complicated to analyze, we would transform it to a simple fuzzy graph by using T-norm family. In addition, to investigate the relations between nodes, we would define the fuzzy contingency table. In this paper, we would discuss about five subjects, (1) new T-norm "Uesu product", (2) fuzzy node fuzzy graph, (3) fuzzy contingency table, (4) entropy measures of fuzziness and (5) decision analysis of the optimal fuzzy graph Gλ0 in the fuzzy graph sequence {Gλ}. By using the fuzzy node fuzzy graph theory, the new T-norm and the fuzzy contingency table, we could clarify the relational structure of fuzzy information. According to the decision method in section 2, we could find the optimal fuzzy graph Gλ0 in the fuzzy graph sequence {G λ}, and clarify the structural feature of the fuzzy node fuzzy graph. Moreover, we would illustrate its practical effectiveness with the case study concerning sociometry analysis.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012
Pages301-306
Number of pages6
DOIs
Publication statusPublished - 2012
Event3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012 - Kaohsiung City
Duration: 2012 Sep 262012 Sep 28

Other

Other3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012
CityKaohsiung City
Period12/9/2612/9/28

Keywords

  • fuzzy node fuzzy graph
  • sociometry analysis
  • T-norm
  • T-norm family

ASJC Scopus subject areas

  • Bioengineering
  • Software

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  • Cite this

    Uesu, H., Kanagawa, S., Shinkai, K., & Nagashima, K. (2012). Analysis of similarity coefficients in fuzzy node fuzzy graph and its application. In Proceedings - 3rd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2012 (pp. 301-306). [6337682] https://doi.org/10.1109/IBICA.2012.32