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

Author:

Kebonye Ndiye M.,Eze Peter N.,John Kingsley,Gholizadeh Asa,Dajčl Julie,Drábek Ondřej,Němeček Karel,Borůvka Luboš

Funder

Grantová Agentura České Republiky

Česká Zemědělská Univerzita v Praze

Publisher

Elsevier BV

Subject

Economic Geology,Geochemistry and Petrology

Reference65 articles.

1. Assessment of self-organizing map artificial neural networks for the classification of sediment quality;Alvarez-Guerra;Environ. Int.,2008

2. Sequential extraction of heavy metals in soils from copper mine: distribution in geochemical fractions;Arenas-Lago;Geoderma,2014

3. Heavy metal distribution between fractions of humic substances in heavily polluted soils;Borůvka;Plant Soil Environ.,2004

4. Litavka river alluvium as a model area heavily polluted with potentially risk elements;Borůvka,2006

5. Principal component analysis as a tool to indicate the origin of potentially toxic elements in soils;Borůvka;Geoderma,2005

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