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Using geostatistics and machine learning models to analyze the influence of soil nutrients and terrain attributes on lead prediction in forest soils
Title Using geostatistics and machine learning models to analyze the influence of soil nutrients and terrain attributes on lead prediction in forest soils Author info Samuel Kudjo Ahado ... [et al.] Author Ahado Samuel Kudjo 1984- (50%) UMBFP09 - Katedra biológie a environmentálnych štúdií
Co-authors Agyeman Prince Chapman (15%)
Borůvka Luboš (15%)
Kanianska Radoslava 1967- (15%) UMBFP09 - Katedra biológie a environmentálnych štúdií
Nwaogu Chukwudi (5%)
Source document Modeling earth systems and environment. Vol. 10, no. 2 (2024), pp. 2099-2112. - Cham : Springer Nature Switzerland AG, 2024 Keywords olovo - lead lesné pôdy pôdne živiny - soil nutrients geoštatistika Form. Descr. články - journal articles Language English Country Germany URL Link na plný text Public work category ADM No. of Archival Copy 54322 Repercussion category KWAYISI, Daniel - KAZAPOE, Raymond Webrah - ALIDU, Seidu - SAGOE, Samuel Dzidefo - UMARU, Aliyu Ohiani - AMUAH, Ebenezer Ebo Yahans - KPIEBAYA, Prosper. Exploring soil pollution patterns in Ghana's 's northeastern mining zone using machine learning models. In Journal of hazardous materials advances. ISSN 2772-4166, 2024, vol. 16, art. no. 100480, pp. 1-13. DOI: https://doi.org/10.1016/j.hazadv.2024.100480
Catal.org. BB301 - Univerzitná knižnica Univerzity Mateja Bela v Banskej Bystrici Database xpca - PUBLIKAČNÁ ČINNOSŤ References PERIODIKÁ-Súborný záznam periodika 
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