IDEAS home Printed from https://ideas.repec.org/a/ids/ijetma/v26y2023i3-4-5p304-315.html
   My bibliography  Save this article

A prediction method of soil environmental pollutants in landscape architecture planning based on data clustering

Author

Listed:
  • Shengli Xu

Abstract

Aiming at the problem of low prediction accuracy in the prediction of soil environmental pollutants in landscape architecture, a prediction method of soil environmental pollutants in landscape architecture planning based on data clustering is designed. Firstly, through the soil pollution evaluation standard in landscape architecture planning, the pollution index system is constructed to obtain the pollution index data. Then, the consistency pre-processing of the obtained pollution index data is carried out, and the data features are extracted with the help of regionalised variables and variogram. Finally, according to the feature extraction results, the pollution weight is determined by Nemero index, and the pollution grade is divided by data clustering method. According to the pollution trend, the prediction model of pollutant soil pollution degree is constructed to complete the prediction. The results show that the proposed method can effectively improve the prediction accuracy of soil pollution.

Suggested Citation

  • Shengli Xu, 2023. "A prediction method of soil environmental pollutants in landscape architecture planning based on data clustering," International Journal of Environmental Technology and Management, Inderscience Enterprises Ltd, vol. 26(3/4/5), pages 304-315.
  • Handle: RePEc:ids:ijetma:v:26:y:2023:i:3/4/5:p:304-315
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=130794
    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.

    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:ids:ijetma:v:26:y:2023:i:3/4/5:p:304-315. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=11 .

    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.