New perspectives and applications of real-time fuzzy regression

Azizul Azhar Ramli, Junzo Watada, Witold Pedrycz

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    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.

    Original languageEnglish
    Title of host publicationIEEE International Conference on Fuzzy Systems
    Pages1451-1456
    Number of pages6
    DOIs
    Publication statusPublished - 2009
    Event2009 IEEE International Conference on Fuzzy Systems - Jeju Island
    Duration: 2009 Aug 202009 Aug 24

    Other

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

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence
    • Applied Mathematics
    • Theoretical Computer Science

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  • Cite this

    Ramli, A. A., Watada, J., & Pedrycz, W. (2009). New perspectives and applications of real-time fuzzy regression. In IEEE International Conference on Fuzzy Systems (pp. 1451-1456). [5277160] https://doi.org/10.1109/FUZZY.2009.5277160