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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8736


    Title: Approximate dominance-based rough sets using equivalence granules
    Authors: Chan, Chien-Chung
    Contributors: Department of Information Science and Applications
    Keywords: Decision making;Decision theory;Fuzzy logic;Fuzzy sets;Fuzzy systems;Learning algorithms;Learning systems;Polynomial approximation;Set theory;Approximation spaces;Data analysis;Decision analysis;Equivalence relations;Lower approximations;Multiple criterions;Rough sets
    Date: 2008
    Issue Date: 2010-04-07 21:34:20 (UTC+8)
    Publisher: Asia University
    Abstract: The rough set theory introduced by Pawlak has provided a solid foundation for developing many useful learning algorithms and tools for data analysis. Dominance-based rough set introduced by Greco et al. is an extension of classical rough sets for dealing with multiple criteria decision analysis problems. In this paper, we look into the relationship between the two theories and introduce a procedure for approximating dominance-based rough sets by a family of equivalence relations. We use the concept of indexed blocks to represent dominance-based approximation space, and it is assumed that the family of indexed blocks forms a partition on the universe of objects. Objects in lower approximations are used to approximate the dominance-based approximation space. An example is given to illustrate the feasibility of our approach. ©2008 IEEE.
    Relation: IEEE International Conference on Fuzzy Systems :2433-2438
    Appears in Collections:[行動商務與多媒體應用學系] 期刊論文

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