Real-time fuzzy regression analysis: A convex hull approach

Azizul Azhar Ramli, Junzo Watada, Witold Pedrycz

    Research output: Contribution to journalArticle

    24 Citations (Scopus)

    Abstract

    In this study, we present an enhancement of fuzzy regression analysis with regard to its aspect of real-time processing. Let us recall that fuzzy regression generalizes the concept of classical (numeric) regression in the sense of bringing additional capabilities that allow the model to deal with fuzzy (granular) data. We show that a convex hull method provides a useful vehicle to reduce computing time, which becomes of particular relevance in case of real-time data analysis. Our objective is to develop an efficient real-time fuzzy regression analysis based on the use of convex hull, specifically a Beneath-Beyond algorithm. In this algorithm, the re-construction of convex hull edges depends on incoming vertices while a re-computing procedure can be realized in real-time. We demonstrate the use of the developed enhancement to application to unit performance assessment and air pollution data. An important role of convex hull is contrasted with the limitations of linear programming used in the "standard" regression.

    Original languageEnglish
    Pages (from-to)606-617
    Number of pages12
    JournalEuropean Journal of Operational Research
    Volume210
    Issue number3
    DOIs
    Publication statusPublished - 2011 May 1

    Fingerprint

    Fuzzy Regression
    Regression Analysis
    Convex Hull
    Regression analysis
    Real-time
    Air pollution
    Linear programming
    Enhancement
    Regression
    Performance Assessment
    Air Pollution
    Computing
    Processing
    Numerics
    Data analysis
    Generalise
    Unit
    Fuzzy regression
    Convex hull
    Demonstrate

    Keywords

    • Convex hull
    • Fuzzy regression analysis
    • Fuzzy set
    • Linear programming
    • Regression analysis

    ASJC Scopus subject areas

    • Management Science and Operations Research
    • Modelling and Simulation
    • Information Systems and Management

    Cite this

    Real-time fuzzy regression analysis : A convex hull approach. / Ramli, Azizul Azhar; Watada, Junzo; Pedrycz, Witold.

    In: European Journal of Operational Research, Vol. 210, No. 3, 01.05.2011, p. 606-617.

    Research output: Contribution to journalArticle

    Ramli, Azizul Azhar ; Watada, Junzo ; Pedrycz, Witold. / Real-time fuzzy regression analysis : A convex hull approach. In: European Journal of Operational Research. 2011 ; Vol. 210, No. 3. pp. 606-617.
    @article{fe934419ad1044a48661d720c29e23ed,
    title = "Real-time fuzzy regression analysis: A convex hull approach",
    abstract = "In this study, we present an enhancement of fuzzy regression analysis with regard to its aspect of real-time processing. Let us recall that fuzzy regression generalizes the concept of classical (numeric) regression in the sense of bringing additional capabilities that allow the model to deal with fuzzy (granular) data. We show that a convex hull method provides a useful vehicle to reduce computing time, which becomes of particular relevance in case of real-time data analysis. Our objective is to develop an efficient real-time fuzzy regression analysis based on the use of convex hull, specifically a Beneath-Beyond algorithm. In this algorithm, the re-construction of convex hull edges depends on incoming vertices while a re-computing procedure can be realized in real-time. We demonstrate the use of the developed enhancement to application to unit performance assessment and air pollution data. An important role of convex hull is contrasted with the limitations of linear programming used in the {"}standard{"} regression.",
    keywords = "Convex hull, Fuzzy regression analysis, Fuzzy set, Linear programming, Regression analysis",
    author = "Ramli, {Azizul Azhar} and Junzo Watada and Witold Pedrycz",
    year = "2011",
    month = "5",
    day = "1",
    doi = "10.1016/j.ejor.2010.10.007",
    language = "English",
    volume = "210",
    pages = "606--617",
    journal = "European Journal of Operational Research",
    issn = "0377-2217",
    publisher = "Elsevier",
    number = "3",

    }

    TY - JOUR

    T1 - Real-time fuzzy regression analysis

    T2 - A convex hull approach

    AU - Ramli, Azizul Azhar

    AU - Watada, Junzo

    AU - Pedrycz, Witold

    PY - 2011/5/1

    Y1 - 2011/5/1

    N2 - In this study, we present an enhancement of fuzzy regression analysis with regard to its aspect of real-time processing. Let us recall that fuzzy regression generalizes the concept of classical (numeric) regression in the sense of bringing additional capabilities that allow the model to deal with fuzzy (granular) data. We show that a convex hull method provides a useful vehicle to reduce computing time, which becomes of particular relevance in case of real-time data analysis. Our objective is to develop an efficient real-time fuzzy regression analysis based on the use of convex hull, specifically a Beneath-Beyond algorithm. In this algorithm, the re-construction of convex hull edges depends on incoming vertices while a re-computing procedure can be realized in real-time. We demonstrate the use of the developed enhancement to application to unit performance assessment and air pollution data. An important role of convex hull is contrasted with the limitations of linear programming used in the "standard" regression.

    AB - In this study, we present an enhancement of fuzzy regression analysis with regard to its aspect of real-time processing. Let us recall that fuzzy regression generalizes the concept of classical (numeric) regression in the sense of bringing additional capabilities that allow the model to deal with fuzzy (granular) data. We show that a convex hull method provides a useful vehicle to reduce computing time, which becomes of particular relevance in case of real-time data analysis. Our objective is to develop an efficient real-time fuzzy regression analysis based on the use of convex hull, specifically a Beneath-Beyond algorithm. In this algorithm, the re-construction of convex hull edges depends on incoming vertices while a re-computing procedure can be realized in real-time. We demonstrate the use of the developed enhancement to application to unit performance assessment and air pollution data. An important role of convex hull is contrasted with the limitations of linear programming used in the "standard" regression.

    KW - Convex hull

    KW - Fuzzy regression analysis

    KW - Fuzzy set

    KW - Linear programming

    KW - Regression analysis

    UR - http://www.scopus.com/inward/record.url?scp=79151469745&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=79151469745&partnerID=8YFLogxK

    U2 - 10.1016/j.ejor.2010.10.007

    DO - 10.1016/j.ejor.2010.10.007

    M3 - Article

    AN - SCOPUS:79151469745

    VL - 210

    SP - 606

    EP - 617

    JO - European Journal of Operational Research

    JF - European Journal of Operational Research

    SN - 0377-2217

    IS - 3

    ER -