A real-time analysis of granular information: Some initial thoughts on a convex hull-based fuzzy regression approach

Azizul Azhar Ramli*, Witold Pedrycz, Junzo Watada, Nureize Arbaiy

*この研究の対応する著者

    研究成果: Conference contribution

    抄録

    Regression models are well known and widely used as one of the important categories of models in system modeling. In this paper, we extend the concept of fuzzy regression in order to handle real-time implementation of data analysis of information granules. An ultimate objective of this study is to develop a hybrid of a genetically-guided clustering algorithm called genetic algorithm-Fuzzy C-Means (GA-FCM) and a convex hull-based fuzzy regression approach being regarded as a potential solution to the formation of information granules. It is anticipated that the setting of Granular Computing will help us reduce the computing time, especially in case of real-time data analysis, as well as an overall computational complexity. We propose an efficient real-time granular fuzzy regression analysis based on the convex hull approach in which a Beneath-Beyond algorithm is employed to design a convex hull. In the proposed design setting, we emphasize a pivotal role of the convex hull approach, which becomes crucial in alleviating limitations of linear programming manifesting in system modeling.

    本文言語English
    ホスト出版物のタイトルIEEE International Conference on Fuzzy Systems
    ページ2851-2858
    ページ数8
    DOI
    出版ステータスPublished - 2011
    イベント2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei
    継続期間: 2011 6 272011 6 30

    Other

    Other2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
    CityTaipei
    Period11/6/2711/6/30

    ASJC Scopus subject areas

    • ソフトウェア
    • 人工知能
    • 応用数学
    • 理論的コンピュータサイエンス

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