Estimation of sodium adsorption ratio in a river with kernel-based and decision-tree models.

Sattari, Mohammad Taghi; Feizi, Hajar; Colak, Muslume Sevba; Ozturk, Ahmet; Apaydin, Halit; Ozturk, Fazli

Sattari, Mohammad Taghi; Feizi, Hajar; Colak, Muslume Sevba; Ozturk, Ahmet; Apaydin, Halit; Ozturk, Fazli.

Afiliação

Sattari MT; Department of Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, 51666, Iran. mohammadtaghisattari@duytan.edu.vn.
Feizi H; Institute of Research and Development, Duy Tan University, Danang, 550000, Vietnam. mohammadtaghisattari@duytan.edu.vn.
Colak MS; Department of Agricultural Engineering, Faculty of Agriculture, Ankara University, Ankara, 06110, Turkey. mohammadtaghisattari@duytan.edu.vn.
Ozturk A; Department of Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, 51666, Iran.
Apaydin H; Department of Agricultural Engineering, Faculty of Agriculture, Ankara University, Ankara, 06110, Turkey.
Ozturk F; Department of Agricultural Engineering, Faculty of Agriculture, Ankara University, Ankara, 06110, Turkey.

Environ Monit Assess ; 192(9): 575, 2020 Aug 09.

Article em En | MEDLINE | ID: mdl-32772253

Assuntos

Rios; Sódio; Adsorção; Monitoramento Ambiental; Turquia

Palavras-chave

Decision-tree models; Kernel functions; Machine learning; Sodium adsorption ratio (SAR); Turkey; Water quality

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation / Prognostic_studies País/Região como assunto: Asia Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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