A constructing algorithm for appropriate piecewise linear membership function based on statistics and information theory

Takashi Hasuike, Hideki Katagiri, Hiroe Tsubaki

研究成果: Conference article査読

8 被引用数 (Scopus)

抄録

This paper proposes a constructing algorithm for an appropriate membership function to integrate the fuzzy Shannon entropy with a piecewise linear function into subjective intervals estimation by the heuristic method based on the human cognitive behavior and subjectivity under a given probability density function. It is important to set a membership function appropriately in real-world decision making. The main parts of our proposed approach are to give membership values a decision maker confidently set, and to obtain the others by solving a nonlinear mathematical programming problem objectively. It is difficult to solve the initial mathematical programming problem efficiently using previous constructing approaches. In this paper, introducing some natural assumptions in the real-world and performing deterministic equivalent transformations to the initial problem using nonlinear programming, an efficient algorithm to obtain the optimal condition of each appropriate membership value is developed.

本文言語English
ページ(範囲)994-1003
ページ数10
ジャーナルProcedia Computer Science
60
1
DOI
出版ステータスPublished - 2015
イベント19th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, KES 2015 - , Singapore
継続期間: 2015 9 72015 9 9

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)

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