Variable precision rough set for group decision-making: An application

Gang Xie, Jinlong Zhang, K. K. Lai, Lean Yu

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    130 Citations (Scopus)

    Abstract

    This study uses the variable precision rough set (VPRS) model as a tool to support group decision-making (GDM) in credit risk management. We consider the case that the classification in decision tables consisting of risk exposure (RE) may be partially erroneous, and use a variable precision factor βk to adjust the classification error. In this paper, we firstly combine VPRS and AHP to obtain the weight of condition attribute sets decided by each decision-maker (DM). Then, the integrated risk exposure (IRE) of attributes is obtained based on the three VPRS-based models. Subsequently, a new procedure of obtaining βk-stable intervals for DMk is investigated. To verify the effectiveness of these proposed methods, an illustrative example is presented. The experimental results suggest that the VPRS-based IRE have advantages in recognizing important attributes. © 2007 Elsevier Inc. All rights reserved.
    Original languageEnglish
    Pages (from-to)331-343
    JournalInternational Journal of Approximate Reasoning
    Volume49
    Issue number2
    DOIs
    Publication statusPublished - Oct 2008

    Research Keywords

    • Analytical hierarchy process
    • Group decision-making
    • Variable precision rough set
    • Weight

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