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
Externally publishedYes

Fingerprint

Membership functions
Probability density function
Entropy
Mathematical programming
Information theory

Keywords

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

ASJC Scopus subject areas

  • Computer Science(all)
  • Control and Systems Engineering

Cite this

Constructing an appropriate membership function integrating fuzzy shannon entropy and human's interval estimation. / Hasuike, Takashi; Katagiri, Hideki; Tsubaki, Hiroe.

In: ICIC Express Letters, Vol. 8, No. 3, 2014, p. 809-813.

Research output: Contribution to journalArticle

@article{db9b5c4e436b4eec8bf0e42740ced435,
title = "Constructing an appropriate membership function integrating fuzzy shannon entropy and human's interval estimation",
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.",
keywords = "Constructing membership function, Fuzzy entropy, Mathematical programming, S-curve function",
author = "Takashi Hasuike and Hideki Katagiri and Hiroe Tsubaki",
year = "2014",
language = "English",
volume = "8",
pages = "809--813",
journal = "ICIC Express Letters",
issn = "1881-803X",
publisher = "ICIC Express Letters Office",
number = "3",

}

TY - JOUR

T1 - Constructing an appropriate membership function integrating fuzzy shannon entropy and human's interval estimation

AU - Hasuike, Takashi

AU - Katagiri, Hideki

AU - Tsubaki, Hiroe

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Constructing membership function

KW - Fuzzy entropy

KW - Mathematical programming

KW - S-curve function

UR - http://www.scopus.com/inward/record.url?scp=84893174591&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84893174591&partnerID=8YFLogxK

M3 - Article

VL - 8

SP - 809

EP - 813

JO - ICIC Express Letters

JF - ICIC Express Letters

SN - 1881-803X

IS - 3

ER -