IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v64y2013i7p1079-1089.html
   My bibliography  Save this article

An approach to decision making based on intuitionistic fuzzy rough sets over two universes

Author

Listed:
  • B Sun

    (1] Tongji University, Shanghai, China[2] Lanzhou Jiaotong University, Lanzhou, China)

  • W Ma

    (Tongji University, Shanghai, China)

  • Q Liu

    (Tongji University, Shanghai, China)

Abstract

Rough set theory has been combined with intuitionistic fuzzy sets in dealing with uncertainty decision making. This paper proposes a general decision-making framework based on the intuitionistic fuzzy rough set model over two universes. We first present the intuitionistic fuzzy rough set model over two universes with a constructive approach and discuss the basic properties of this model. We then give a new approach of decision making in uncertainty environment by using the intuitionistic fuzzy rough sets over two universes. Further, the principal steps of the decision method established in this paper are presented in detail. Finally, an example of handling medical diagnosis problem illustrates this approach.

Suggested Citation

  • B Sun & W Ma & Q Liu, 2013. "An approach to decision making based on intuitionistic fuzzy rough sets over two universes," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(7), pages 1079-1089, July.
  • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:7:p:1079-1089
    as

    Download full text from publisher

    File URL: http://www.palgrave-journals.com/jors/journal/v64/n7/pdf/jors201275a.pdf
    File Function: Link to full text PDF
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: http://www.palgrave-journals.com/jors/journal/v64/n7/full/jors201275a.html
    File Function: Link to full text HTML
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Abbas Mardani & Mehrbakhsh Nilashi & Jurgita Antucheviciene & Madjid Tavana & Romualdas Bausys & Othman Ibrahim, 2017. "Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature," Complexity, Hindawi, vol. 2017, pages 1-33, October.
    2. R. Mareay & Ibrahim Noaman & Radwan Abu-Gdairi & M. Badr, 2022. "On Covering-Based Rough Intuitionistic Fuzzy Sets," Mathematics, MDPI, vol. 10(21), pages 1-8, November.

    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:pal:jorsoc:v:64:y:2013:i:7:p:1079-1089. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.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.