Constructing an appropriate membership function integrating fuzzy shannon entropy and human's interval estimation

Takashi Hasuike, Hideki Katagiri, Hiroe Tsubaki

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

This paper proposes a new approach of constructing an appropriate membership function to integrate a specific given probability density function, particularly Gaussian function, and fuzzy Shannon entropy extending the information theory based on the human cognitive behavior and subjectivity. The proposed approach is formulated as a more general mathematical programming problem than previous approaches due to using a general Gaussian-based function and the fuzzy Shannon entropy. The optimal condition of parameters is obtained by performing deterministic equivalent transformations to the initial problem. Furthermore, in order to show the appropriate membership function using the proposed approach, some probability density functions are provided as numerical examples.

Original languageEnglish
Pages (from-to)809-813
Number of pages5
JournalICIC Express Letters
Volume8
Issue number3
Publication statusPublished - 2014 Feb 4
Externally publishedYes

Keywords

  • Constructing membership function
  • Fuzzy entropy
  • Mathematical programming
  • S-curve function

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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