Self-organizing map artificial neural networks and sequential Gaussian simulation technique for mapping potentially toxic element hotspots in polluted mining soils

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F21%3A84641" target="_blank" >RIV/60460709:41210/21:84641 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0375674220306403" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0375674220306403</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.gexplo.2020.106680" target="_blank" >10.1016/j.gexplo.2020.106680</a>

Result language
angličtina
Original language name
Self-organizing map artificial neural networks and sequential Gaussian simulation technique for mapping potentially toxic element hotspots in polluted mining soils
Original language description
The application of multivariate geostatistical and statistical methods remain valuable tools for environmental pollution assessment. In particular, stochastic simulation techniques like sequential Gaussian simulation SGS and the self organizing map artificial neural networks SeOM ANNs have facilitated the understanding of the spatial distribution of potentially toxic elements PTEs in polluted soils. However, there is a dearth of literature on the application of SGS and SeOM ANN in mapping potentially toxic elements PTE in heavily polluted mining and smelter affected floodplain soils. This study shows the applicability SGS and SeOM ANN which is a powerful visualization tool for the categorization of PTEs Cadmium Cd, Arsenic As, Antimony Sb, Lead Pb and Zinc Zn levels together with selected soil properties oxidizable carbon Cox and soil reaction pH H2O in one of the most polluted mining floodplain soils in Europe. A k means algorithm was used to classify distinct clusters which were visually unclear ba
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
40104 - Soil science

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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