IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v231y2013i1p162-170.html
   My bibliography  Save this article

Information granulation and uncertainty measures in interval-valued intuitionistic fuzzy information systems

Author

Listed:
  • Huang, Bing
  • Zhuang, Yu-liang
  • Li, Hua-xiong

Abstract

Information granulation and entropy are main approaches for investigating the uncertainty of information systems, which have been widely employed in many practical domains. In this paper, information granulation and uncertainty measures for interval-valued intuitionistic fuzzy binary granular structures are addressed. First, we propose the representation of interval-valued intuitionistic fuzzy information granules and examine some operations of interval-valued intuitionistic fuzzy granular structures. Second, the interval-valued intuitionistic fuzzy information granularity is introduced to depict the distinguishment ability of an interval-valued intuitionistic fuzzy granular structure (IIFGS), which is a natural extension of fuzzy information granularity. Third, we discuss how to scale the uncertainty of an IIFGS using the extended information entropy and the uncertainty among interval-valued intuitionistic fuzzy granular structures using the expanded mutual information derived from the presented intuitionistic fuzzy information entropy. Fourth, we discovery the relationship between the developed interval-valued intuitionistic fuzzy information entropy and the intuitionistic fuzzy information granularity presented in this paper.

Suggested Citation

  • Huang, Bing & Zhuang, Yu-liang & Li, Hua-xiong, 2013. "Information granulation and uncertainty measures in interval-valued intuitionistic fuzzy information systems," European Journal of Operational Research, Elsevier, vol. 231(1), pages 162-170.
  • Handle: RePEc:eee:ejores:v:231:y:2013:i:1:p:162-170
    DOI: 10.1016/j.ejor.2013.05.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221713003901
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2013.05.006?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
    ---><---

    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. Du, Wen Sheng & Hu, Bao Qing, 2017. "Dominance-based rough fuzzy set approach and its application to rule induction," European Journal of Operational Research, Elsevier, vol. 261(2), pages 690-703.
    2. Rafał Kozik & Marek Pawlicki & Michał Choraś & Witold Pedrycz, 2019. "Practical Employment of Granular Computing to Complex Application Layer Cyberattack Detection," Complexity, Hindawi, vol. 2019, pages 1-9, January.
    3. Ouyang, Yao & Pedrycz, Witold, 2016. "A new model for intuitionistic fuzzy multi-attributes decision making," European Journal of Operational Research, Elsevier, vol. 249(2), pages 677-682.

    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:eee:ejores:v:231:y:2013:i:1:p:162-170. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.