| Autor: |
Stojić N; Faculty of Environmental Protection, Educons University, 21208 Sremska Kamenica, Serbia., Pezo L; Institute of General and Physical Chemistry, University of Belgrade, 11000 Belgrade, Serbia., Lončar B; Faculty of Technology Novi Sad, University of Novi Sad, 21000 Novi Sad, Serbia., Pucarević M; Faculty of Environmental Protection, Educons University, 21208 Sremska Kamenica, Serbia., Filipović V; Faculty of Technology Novi Sad, University of Novi Sad, 21000 Novi Sad, Serbia., Prokić D; Faculty of Environmental Protection, Educons University, 21208 Sremska Kamenica, Serbia., Ćurčić L; Faculty of Environmental Protection, Educons University, 21208 Sremska Kamenica, Serbia., Štrbac S; Institute of Chemistry, Technology and Metallurgy, University of Belgrade, 11000 Belgrade, Serbia. |
| Abstrakt: |
The main objective of this study is to determine the possibility of predicting the impact of land use and soil type on concentrations of heavy metals (HMs) and phthalates (PAEs) in soil based on an artificial neural network model (ANN). Qualitative analysis of HMs was performed with inductively coupled plasma-optical emission spectrometry (ICP/OES) and Direct Mercury Analyzer. Determination of PAEs was performed with gas chromatography (GC) coupled with a single quadrupole mass spectrometry (MS). An ANN, based on the Broyden-Fletcher-Goldfarb-Shanno (BFGS) iterative algorithm, for the prediction of HM and PAE concentrations, based on land use and soil type parameters, showed good prediction capabilities (the coefficient of determination ( r 2 ) values during the training cycle for HM concentration variables were 0.895, 0.927, 0.885, 0.813, 0.883, 0.917, 0.931, and 0.883, respectively, and for PAEs, the concentration variables were 0.950, 0.974, 0.958, 0.974, and 0.943, respectively). The results of this study indicate that HM and PAE concentrations, based on land use and soil type, can be predicted using ANN. |
