Journal of New Approaches in Water Engineering and Environment
Scientific Journal

Nitrate adsorption modeling using SVM and LSSVM models

Document Type : Original Article

Authors

Masumeh Farasati 1
Seyed Morteza seyedian 1
seyed Javad sajadi 2

1 Department of water engineering, faculty of agriculture and natural resource, Gonbad kavous University, Gonbad kavous, Iran.

2 Department of plant production, faculty of agriculture and natural resource, Gonbad kavous University, Gonbad kavous, Iran.

https://doi.org/10.22034/nawee.2025.510813.1145
Abstract
Nitrate compounds are among the pollutants of groundwater resources that in recent years in terms of agricultural development and human activities, their average rate is increasing. This ion may enter drinking water as it passes through the ground, or it may enter groundwater sources as a result of water contamination with organic matter and the accumulation of municipal and industrial waste, or the accumulation of animal and chemical fertilizers or the leakage of municipal sewage facilities. But in recent decades, increasing use of nitrogen fertilizers has led to the addition of nitrate in surface and groundwater.

The data used in this study were first randomized and standardized and then divided into two groups of training and testing. 70% of the data were in the training group and the remaining 30% in the experimental group. Validation of model training was performed using k-fold cross validation method with a value of k = 5 in order to prevent over-fitting of models. The parameters of Random Forest, SVM and LS-SVM models were determined using Bayesian optimization algorithm. The objective function of the optimization algorithm was to minimize the MSE error value of the model. Based on the results, the Random Forest model was used with the Bagging algorithm and the parameters of minimum node size, number of trees and number of variables used were equal to 2, 10 and 3, respectively.

Keywords

Nitrate
adsorption
SVM
lssvm
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Journal of New Approaches in Water Engineering and Environment
Volume 4, Issue 2
Special Issue: Guest Editor: Prof. Ozgur Kisi
September 2025
Pages 160-179

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