Fuzzy Node Fuzzy Graph Analysis Applying T-norm

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概要

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• The authors could generally analyze the inexact information efficiently 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. And we transform it to a fuzzy graph by using T-norm family. In this paper, we would discuss about four subjects, (1) fuzzy node fuzzy graph, (2) new T-norm "quasi logical product", (3) decision analysis of the optimal fuzzy graph in the Juzzy graph sequence. By using the fuzzy node fuzzy graph theory and this new T-norm, we could clarify the relational structure of fuzzy information, and by using the decision of an optimal level on a partition tree, we could analyze the clustering relation among nodes. Moreover, we would illustrate its practical effectiveness with the case study concerning sociometry analysis.

• バイオメディカル・ファジィ・システム学会の論文
• 2009-10-10

著者

• Kanagawa Shuya

  Tokyo City University

• UESU Hiroaki

  Waseda University

関連論文

• Fuzzy Node Fuzzy Graph Analysis Applying T-norm
• Structure Analysis of Fuzzy Node Fuzzy Graph and its Application
• Fuzzy Node Fuzzy Graph Analysis Applying T-norm(New Development of SOFT Science in BMFSA2009-AMAMI)

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