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

Authors: Shengli Xu

Addresses: Department of Landscape Architecture, Xi'an International University, Xi'an 710077, China

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.

Keywords: data clustering; landscape architecture; soil environmental pollutants; similarity matrix.

DOI: 10.1504/IJETM.2023.130794

International Journal of Environmental Technology and Management, 2023 Vol.26 No.3/4/5, pp.304 - 315

Received: 01 Mar 2022
Accepted: 31 May 2022
Published online: 07 May 2023 *

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