IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v51y2020i11p1945-1958.html
   My bibliography  Save this article

A kriging method for fuzzy spatial data

Author

Listed:
  • Gholamreza Hesamian
  • Mohamad Ghasem Akbari

Abstract

This paper extends the ordinary kriging prediction method and proposes a trend removal method for observed spatial data represented as LR-fuzzy numbers. To this end, a covariance concept was developed and discussed in the fuzzy domain. Then, a notion of semi-variogram and its empirical estimator were proposed. The proposed semi-variogram exhibited all of the characteristics of a typical semi-variogram in the fuzzy domain. A non-parametric kernel-based method was proposed to remove the trend across the fuzzy data. Some common goodness-of-fit criteria were employed to examine the performance of the proposed kriging prediction method. The proposed method was then put to test using a simulated set of fuzzy data. In order to demonstrate the applicability of this approach, it was applied to a set of pH data in the fuzzy domain to investigate the quality of groundwater. The results proved the potentials of the proposed method for the fuzzy spatial data encountered in real applications.

Suggested Citation

  • Gholamreza Hesamian & Mohamad Ghasem Akbari, 2020. "A kriging method for fuzzy spatial data," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(11), pages 1945-1958, July.
    • Handle: RePEc:taf:tsysxx:v:51:y:2020:i:11:p:1945-1958
    DOI: 10.1080/00207721.2020.1781288
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2020.1781288
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2020.1781288?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.

    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:taf:tsysxx:v:51:y:2020:i:11:p:1945-1958. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    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.