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Ping Zhu

  1. Homomorphisms between fuzzy information systems revisited.

    Пт, 02/05/2010 - 16:01 — SomNambul
    Authors: Ping Zhu, Qiaoyan Wen
    Subjects: Artificial Intelligence
    Abstract

    Recently, Wang et al. discussed the properties of fuzzy information systems
    under homomorphisms in the paper [C. Wang, D. Chen, L. Zhu, Homomorphisms
    between fuzzy information systems, Applied Mathematics Letters 22 (2009)
    1045-1050], where homomorphisms are based upon the concepts of consistent
    functions and fuzzy relation mappings. In this paper, we classify consistent
    functions as predecessor-consistent and successor-consistent, and then proceed
    to present more properties of consistent functions.

  2. A note on "communicating between information systems".

    Ср, 02/03/2010 - 16:01 — SomNambul
    Authors: Ping Zhu, Qiaoyan Wen
    Subjects: Artificial Intelligence
    Abstract

    This note is an amendment to a paper by Wang et al. [C. Wang, C. Wu, D. Chen,
    Q. Hu, and C. Wu, Communicating between information systems, Information
    Sciences 178 (2008) 3228-3239]. To study the communication between two
    information systems, Wang et al. proposed two concepts of type-1 and type-2
    consistent functions. Some good properties of consistent functions and induced
    relation mappings have been investigated there. In this paper, we provide an
    improvement of the aforementioned work by disclosing the symmetric relationship
    between type-1 and type-2 consistent functions.

  3. An axiomatic approach to the roughness measure of rough sets.

    Втр, 12/01/2009 - 16:02 — SomNambul
    Authors: Ping Zhu
    Subjects: Artificial Intelligence
    Abstract

    In Pawlak's rough set theory, each rough set is approximated by a pair of
    lower and upper approximations. To measure numerically the roughness of an
    approximation, Pawlak introduced a quantitative measure of roughness by using
    the ratio of the cardinalities of the lower and upper approximations. Although
    the roughness measure is effective, it has the drawback of not being strictly
    monotonic with respect to the standard ordering on partitions. Recently, some
    improvements have been made by taking into account the granularity of
    partitions.

  4. Covering rough sets based on neighborhoods.

    Втр, 12/01/2009 - 16:02 — SomNambul
    Authors: Ping Zhu
    Subjects: Artificial Intelligence
    Abstract

    Rough set theory, a mathematical tool to deal with vague concepts, has
    originally described the indiscernibility of elements by equivalence relations.
    Covering rough sets are a natural extension of classical rough sets by relaxing
    the partitions arising from equivalence relations to covers. Recently, some
    topological concepts such as neighborhood have been applied to covering rough
    sets. In this paper, we further investigate the covering rough sets based on
    neighborhoods by approximation operations.

  5. An improved axiomatic definition of information granulation.

    Пт, 08/28/2009 - 23:56 — SomNambul
    Authors: Ping Zhu
    Subjects: Artificial Intelligence
    Abstract

    To capture the uncertainty of information or knowledge in information
    systems, various information granulations, also known as knowledge
    granulations, have been proposed. Recently, several axiomatic definitions of
    information granulation have been introduced. In this paper, we try to improve
    these axiomatic definitions and give a universal construction of information
    granulation by relating information granulations with a class of functions of
    multiple variables. We show that the improved axiomatic definition has some
    concrete information granulations in the literature as instances.

Math-arch

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