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Application of artificial neural network and dynamic adsorption models to predict humic substances extraction from municipal solid waste leachate.
Rezaeinia, Salimeh; Ebrahimi, Ali Asghar; Dalvand, Arash; Ehrampoush, Mohammad Hassan; Fallahzadeh, Hossien; Mokhtari, Mehdi.
Afiliação
  • Rezaeinia S; Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
  • Ebrahimi AA; Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
  • Dalvand A; Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
  • Ehrampoush MH; Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
  • Fallahzadeh H; Department of Biostatistics and Epidemiology, Research Center of Prevention and Epidemiology of Non­Communicable Disease, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
  • Mokhtari M; Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. mokhtari@ssu.ac.ir.
Sci Rep ; 13(1): 12421, 2023 Aug 01.
Article em En | MEDLINE | ID: mdl-37528123
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Irã País de publicação: Reino Unido
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Irã País de publicação: Reino Unido