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A physics-informed statistical learning framework for forecasting local suspended sediment concentrations in marine environment.
Zhang, Shaotong; Wu, Jinran; Wang, You-Gan; Jeng, Dong-Sheng; Li, Guangxue.
Afiliação
  • Zhang S; Key Laboratory for Submarine Geosciences and Prospecting Techniques (State Ministry of Education), College of Marine Geosciences, Ocean University of China, Qingdao 266100, China; Shandong Provincial Key Laboratory for Marine Environment and Geological Engineering, College of Environmental Science a
  • Wu J; School of Mathematical Sciences, Queensland University of Technology, QLD 4001, Australia. Electronic address: j73.wu@qut.edu.au.
  • Wang YG; School of Mathematical Sciences, Queensland University of Technology, QLD 4001, Australia. Electronic address: you-gan.wang@qut.edu.au.
  • Jeng DS; School of Engineering & Built Environment, Griffith University Gold Coast Campus, QLD 4222, Australia. Electronic address: d.jeng@griffith.edu.au.
  • Li G; Key Laboratory for Submarine Geosciences and Prospecting Techniques (State Ministry of Education), College of Marine Geosciences, Ocean University of China, Qingdao 266100, China. Electronic address: estuary@ouc.edu.cn.
Water Res ; 218: 118518, 2022 Jun 30.
Article em En | MEDLINE | ID: mdl-35526355
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Qualidade da Água / Rios Tipo de estudo: Prognostic_studies Idioma: En Revista: Water Res Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Qualidade da Água / Rios Tipo de estudo: Prognostic_studies Idioma: En Revista: Water Res Ano de publicação: 2022 Tipo de documento: Article