IDEAS home Printed from https://ideas.repec.org/a/hin/jnlaaa/183410.html
   My bibliography  Save this article

A Dynamic Fuzzy Cluster Algorithm for Time Series

Author

Listed:
  • Min Ji
  • Fuding Xie
  • Yu Ping

Abstract

This paper presents an efficient algorithm, called dynamic fuzzy cluster (DFC), for dynamically clustering time series by introducing the definition of key point and improving FCM algorithm. The proposed algorithm works by determining those time series whose class labels are vague and further partitions them into different clusters over time. The main advantage of this approach compared with other existing algorithms is that the property of some time series belonging to different clusters over time can be partially revealed. Results from simulation-based experiments on geographical data demonstrate the excellent performance and the desired results have been obtained. The proposed algorithm can be applied to solve other clustering problems in data mining.

Suggested Citation

  • Min Ji & Fuding Xie & Yu Ping, 2013. "A Dynamic Fuzzy Cluster Algorithm for Time Series," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-7, April.
    • Handle: RePEc:hin:jnlaaa:183410
    DOI: 10.1155/2013/183410
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/AAA/2013/183410.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/AAA/2013/183410.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2013/183410?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. Ignacio Benítez & José-Luis Díez, 2022. "Automated Detection of Electric Energy Consumption Load Profile Patterns," Energies, MDPI, vol. 15(6), pages 1-26, March.

    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:jnlaaa:183410. 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.