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Journal Abstract Search

115 related items for PubMed ID: 36881245

  • 1. Determination of conditioning factors for mapping nickel contamination susceptibility in groundwater in Kanchanaburi Province, Thailand, using random forest and maximum entropy.
    Thanh NN, Chotpantarat S, Ha NT, Trung NH.
    Environ Geochem Health; 2023 Jul; 45(7):4583-4602. PubMed ID: 36881245
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  • 2. Integrating machine learning models with cross-validation and bootstrapping for evaluating groundwater quality in Kanchanaburi province, Thailand.
    Thanh NN, Chotpantarat S, Ngu NH, Thunyawatcharakul P, Kaewdum N.
    Environ Res; 2024 Jul 01; 252(Pt 2):118952. PubMed ID: 38636644
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  • 3. The risk assessment of arsenic contamination in the urbanized coastal aquifer of Rayong groundwater basin, Thailand using the machine learning approach.
    Sumdang N, Chotpantarat S, Cho KH, Thanh NN.
    Ecotoxicol Environ Saf; 2023 Mar 15; 253():114665. PubMed ID: 36863158
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  • 7. Groundwater salinity modeling and mapping using machine learning approaches: a case study in Sidi Okba region, Algeria.
    Boudibi S, Fadlaoui H, Hiouani F, Bouzidi N, Aissaoui A, Khomri ZE.
    Environ Sci Pollut Res Int; 2024 Aug 15; 31(36):48955-48971. PubMed ID: 39042194
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  • 9. Susceptibility Assessment of Groundwater Nitrate Contamination Using an Ensemble Machine Learning Approach.
    Hosseini FS, Choubin B, Bagheri-Gavkosh M, Karimi O, Taromideh F, Mako C.
    Ground Water; 2023 Aug 15; 61(4):510-516. PubMed ID: 36127852
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  • 10. Application of rotation forest with decision trees as base classifier and a novel ensemble model in spatial modeling of groundwater potential.
    Naghibi SA, Dolatkordestani M, Rezaei A, Amouzegari P, Heravi MT, Kalantar B, Pradhan B.
    Environ Monit Assess; 2019 Mar 27; 191(4):248. PubMed ID: 30919064
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  • 11. A novel ensemble model of automatic multilayer perceptron, random forest, and ZeroR for groundwater potential mapping.
    Sachdeva S, Kumar B.
    Environ Monit Assess; 2021 Oct 14; 193(11):722. PubMed ID: 34648078
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  • 12. The potential evaluation of groundwater by integrating rank sum ratio (RSR) and machine learning algorithms in the Qaidam Basin.
    Wang Z, Wang J, Yu D, Chen K.
    Environ Sci Pollut Res Int; 2023 May 14; 30(23):63991-64005. PubMed ID: 37059956
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  • 19. Assessing data mining algorithms to predict the quality of groundwater resources for determining irrigation hazard.
    Masoudi R, Mousavi SR, Rahimabadi PD, Panahi M, Rahmani A.
    Environ Monit Assess; 2023 Jan 23; 195(2):319. PubMed ID: 36683118
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