Evaluation of parametric and nonparametric machine-learning techniques for prediction of saturated and near-saturated hydraulic conductivity (2019)
- Authors:
- Autor USP: LIER, QUIRIJN DE JONG VAN - CENA
- Unidade: CENA
- DOI: 10.2136/vzj2018.07.0141
- Assunto: CONDUTIVIDADE HIDRÁULICA DO SOLO
- Language: Inglês
- Imprenta:
- Source:
- Título: Vadose Zone Journal
- Volume/Número/Paginação/Ano: v. 18, n. 1, 2019
- Status:
- Artigo publicado em periódico de acesso aberto (Gold Open Access)
- Versão do Documento:
- Versão publicada (Published version)
- Acessar versão aberta:
-
ABNT
MEHMANDOOST, Ali e DE JONG VAN LIER, Quirijn e IVERSEN, Bo V. Evaluation of parametric and nonparametric machine-learning techniques for prediction of saturated and near-saturated hydraulic conductivity. Vadose Zone Journal, v. 18, n. 1, 2019Tradução . . Disponível em: https://doi.org/10.2136/vzj2018.07.0141. Acesso em: 29 mar. 2026. -
APA
Mehmandoost, A., De Jong Van Lier, Q., & Iversen, B. V. (2019). Evaluation of parametric and nonparametric machine-learning techniques for prediction of saturated and near-saturated hydraulic conductivity. Vadose Zone Journal, 18( 1). doi:10.2136/vzj2018.07.0141 -
NLM
Mehmandoost A, De Jong Van Lier Q, Iversen BV. Evaluation of parametric and nonparametric machine-learning techniques for prediction of saturated and near-saturated hydraulic conductivity [Internet]. Vadose Zone Journal. 2019 ; 18( 1):[citado 2026 mar. 29 ] Available from: https://doi.org/10.2136/vzj2018.07.0141 -
Vancouver
Mehmandoost A, De Jong Van Lier Q, Iversen BV. Evaluation of parametric and nonparametric machine-learning techniques for prediction of saturated and near-saturated hydraulic conductivity [Internet]. Vadose Zone Journal. 2019 ; 18( 1):[citado 2026 mar. 29 ] Available from: https://doi.org/10.2136/vzj2018.07.0141 - Determining soil hydraulic properties using gamma-ray attenuation in an evaporation experiment
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