New perspectives and applications of real-time fuzzy regression

Azizul Azhar Ramli, Junzo Watada, Witold Pedrycz

    研究成果: Conference contribution

    1 被引用数 (Scopus)

    抄録

    Fuzzy regression is one of important methods for data analysis. Fuzzy regression extends the concept of classical regression which has been constructed in the statistical framework. We show that a convex hull method can provide a powerful tool to reduce the computing time, especially for real-time data analysis. The main objective of this study is to propose an efficient real-time fuzzy regression analysis based on the use of convex hull, specifically a Beneath-Beyond algorithm. The reconstruction of convex hull edges depends on incoming vertices while a recomputing procedure can be implemented in real-time. An air pollution data is analyzed by applying the proposed approach. An important role of convex hull is emphasized in particular when dealing with the limitations of linear programming.

    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1451-1456
    ページ数6
    DOI
    出版ステータスPublished - 2009
    イベント2009 IEEE International Conference on Fuzzy Systems - Jeju Island
    継続期間: 2009 8 202009 8 24

    Other

    Other2009 IEEE International Conference on Fuzzy Systems
    CityJeju Island
    Period09/8/2009/8/24

    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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