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 contribution

    8 引用 (Scopus)

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    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.

    元の言語English
    ホスト出版物のタイトルProcedia Computer Science
    出版者Elsevier
    ページ994-1003
    ページ数10
    60
    エディション1
    DOI
    出版物ステータス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

    Other

    Other19th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, KES 2015
    Singapore
    期間15/9/715/9/9

    ASJC Scopus subject areas

    • Computer Science(all)

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