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Prediction of long-term water quality using machine learning enhanced by Bayesian optimisation.
Yan, Tao; Zhou, Annan; Shen, Shui-Long.
Afiliação
  • Yan T; MOE Key Laboratory of Intelligent Manufacturing Technology, Department of Civil and Environmental Engineering, College of Engineering, Shantou University, Shantou, Guangdong, 515063, China; Discipline of Civil and Infrastructure Engineering, School of Engineering, Royal Melbourne Institute of Technology (RMIT), Victoria, 3001, Australia. Electronic address: yantao@stu.edu.cn.
  • Zhou A; Discipline of Civil and Infrastructure Engineering, School of Engineering, Royal Melbourne Institute of Technology (RMIT), Victoria, 3001, Australia. Electronic address: annan.zhou@rmit.edu.au.
  • Shen SL; MOE Key Laboratory of Intelligent Manufacturing Technology, Department of Civil and Environmental Engineering, College of Engineering, Shantou University, Shantou, Guangdong, 515063, China. Electronic address: shensl@stu.edu.cn.
Environ Pollut ; 318: 120870, 2023 Feb 01.
Article em En | MEDLINE | ID: mdl-36526051
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Químicos da Água / Qualidade da Água Tipo de estudo: Prognostic_studies / Risk_factors_studies País/Região como assunto: Asia Idioma: En Revista: Environ Pollut Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Químicos da Água / Qualidade da Água Tipo de estudo: Prognostic_studies / Risk_factors_studies País/Região como assunto: Asia Idioma: En Revista: Environ Pollut Ano de publicação: 2023 Tipo de documento: Article