IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/4819353.html
   My bibliography  Save this article

On Characterization of Rough Type-2 Fuzzy Sets

Author

Listed:
  • Tao Zhao
  • Zhenbo Wei

Abstract

Rough sets theory and fuzzy sets theory are important mathematical tools to deal with uncertainties. Rough fuzzy sets and fuzzy rough sets as generalizations of rough sets have been introduced. Type-2 fuzzy set provides additional degree of freedom, which makes it possible to directly handle high uncertainties. In this paper, the rough type-2 fuzzy set model is proposed by combining the rough set theory with the type-2 fuzzy set theory. The rough type-2 fuzzy approximation operators induced from the Pawlak approximation space are defined. The rough approximations of a type-2 fuzzy set in the generalized Pawlak approximation space are also introduced. Some basic properties of the rough type-2 fuzzy approximation operators and the generalized rough type-2 fuzzy approximation operators are discussed. The connections between special crisp binary relations and generalized rough type-2 fuzzy approximation operators are further examined. The axiomatic characterization of generalized rough type-2 fuzzy approximation operators is also presented. Finally, the attribute reduction of type-2 fuzzy information systems is investigated.

Suggested Citation

  • Tao Zhao & Zhenbo Wei, 2016. "On Characterization of Rough Type-2 Fuzzy Sets," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-13, February.
    • Handle: RePEc:hin:jnlmpe:4819353
    DOI: 10.1155/2016/4819353
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2016/4819353.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2016/4819353.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2016/4819353?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. You, Xingxing & Shi, Mingyang & Guo, Bin & Zhu, Yuqi & Lai, Wuxing & Dian, Songyi & Liu, Kai, 2022. "Event-triggered adaptive fuzzy tracking control for a class of fractional-order uncertain nonlinear systems with external disturbance," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    2. Vladik Kreinovich & Olga Kosheleva & Patricia Melin & Oscar Castillo, 2022. "Efficient Algorithms for Data Processing under Type-3 (and Higher) Fuzzy Uncertainty," Mathematics, MDPI, vol. 10(13), pages 1-15, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:4819353. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.