IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/3713518.html
   My bibliography  Save this article

An Intelligent Complex Event Processing with Numbers under Fuzzy Environment

Author

Listed:
  • Fuyuan Xiao

Abstract

Efficient matching of incoming mass events to persistent queries is fundamental to complex event processing systems. Event matching based on pattern rule is an important feature of complex event processing engine. However, the intrinsic uncertainty in pattern rules which are predecided by experts increases the difficulties of effective complex event processing. It inevitably involves various types of the intrinsic uncertainty, such as imprecision, fuzziness, and incompleteness, due to the inability of human beings subjective judgment. Nevertheless, D numbers is a new mathematic tool to model uncertainty, since it ignores the condition that elements on the frame must be mutually exclusive. To address the above issues, an intelligent complex event processing method with D numbers under fuzzy environment is proposed based on the Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method. The novel method can fully support decision making in complex event processing systems. Finally, a numerical example is provided to evaluate the efficiency of the proposed method.

Suggested Citation

  • Fuyuan Xiao, 2016. "An Intelligent Complex Event Processing with Numbers under Fuzzy Environment," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-10, September.
  • Handle: RePEc:hin:jnlmpe:3713518
    DOI: 10.1155/2016/3713518
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2016/3713518.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2016/3713518.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2016/3713518?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. Jianhua Wang & Bang Ji & Feng Lin & Shilei Lu & Yubin Lan & Lianglun Cheng, 2020. "A multiple pattern complex event detection scheme based on decomposition and merge sharing for massive event streams," International Journal of Distributed Sensor Networks, , vol. 16(10), pages 15501477209, October.

    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:3713518. 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.