Relational structure analysis of fuzzy graph and its application: For analyzing fuzzy data of human relation

Hiroaki Uesu, Kenichi Nagashima, Hsunhsun Chung, Ei Tsuda

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

4 Citations (Scopus)

Abstract

Generally, we could efficiently analyze the inexact information and investigate the fuzzy relation by applying the fuzzy graph theory[1]. 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) decision analysis of the optimal fuzzy graph Gλ0 in the fuzzy graph sequence {Gλ} and (5) its application to sociometry analysis. 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 G0 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 publicationIEEE International Conference on Fuzzy Systems
Pages1593-1597
Number of pages5
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei
Duration: 2011 Jun 272011 Jun 30

Other

Other2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
CityTaipei
Period11/6/2711/6/30

Fingerprint

Fuzzy Graph
Fuzzy Data
Graph theory
Decision theory
T-norm
Contingency Table
Vertex of a graph
Human
Decision Analysis
Fuzzy Information
Fuzzy Relation
Simple Graph

Keywords

  • contingency table
  • fuzzy node fuzzy graph
  • optimal fuzzy graph
  • sociometry analysis
  • T-norm

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Applied Mathematics
  • Theoretical Computer Science

Cite this

Uesu, H., Nagashima, K., Chung, H., & Tsuda, E. (2011). Relational structure analysis of fuzzy graph and its application: For analyzing fuzzy data of human relation. In IEEE International Conference on Fuzzy Systems (pp. 1593-1597). [6007573] https://doi.org/10.1109/FUZZY.2011.6007573

Relational structure analysis of fuzzy graph and its application : For analyzing fuzzy data of human relation. / Uesu, Hiroaki; Nagashima, Kenichi; Chung, Hsunhsun; Tsuda, Ei.

IEEE International Conference on Fuzzy Systems. 2011. p. 1593-1597 6007573.

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

Uesu, H, Nagashima, K, Chung, H & Tsuda, E 2011, Relational structure analysis of fuzzy graph and its application: For analyzing fuzzy data of human relation. in IEEE International Conference on Fuzzy Systems., 6007573, pp. 1593-1597, 2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011, Taipei, 11/6/27. https://doi.org/10.1109/FUZZY.2011.6007573
Uesu H, Nagashima K, Chung H, Tsuda E. Relational structure analysis of fuzzy graph and its application: For analyzing fuzzy data of human relation. In IEEE International Conference on Fuzzy Systems. 2011. p. 1593-1597. 6007573 https://doi.org/10.1109/FUZZY.2011.6007573
Uesu, Hiroaki ; Nagashima, Kenichi ; Chung, Hsunhsun ; Tsuda, Ei. / Relational structure analysis of fuzzy graph and its application : For analyzing fuzzy data of human relation. IEEE International Conference on Fuzzy Systems. 2011. pp. 1593-1597
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