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An Integrated First Principal and Deep Learning Approach for Modeling Nitrous Oxide Emissions from Wastewater Treatment Plants.
Li, Kaili; Duan, Haoran; Liu, Linfeng; Qiu, Ruihong; van den Akker, Ben; Ni, Bing-Jie; Chen, Tong; Yin, Hongzhi; Yuan, Zhiguo; Ye, Liu.
Afiliação
  • Li K; School of Chemical Engineering, The University of Queensland, Brisbane, Queensland 4072, Australia.
  • Duan H; School of Chemical Engineering, The University of Queensland, Brisbane, Queensland 4072, Australia.
  • Liu L; Australian Centre for Water and Environmental Biotechnology (formerly AWMC), The University of Queensland, Brisbane, Queensland 4072, Australia.
  • Qiu R; Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia.
  • van den Akker B; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland 4072, Australia.
  • Ni BJ; South Australian Water Corporation, Adelaide, South Australia 5000, Australia.
  • Chen T; School of Natural and Built Environments, University of South Australia, Adelaide, South Australia 5001, Australia.
  • Yin H; College of Science and Engineering, Flinders University, Adelaide, South Australia 5042, Australia.
  • Yuan Z; Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Sydney, New South Wales 2007, Australia.
  • Ye L; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland 4072, Australia.
Environ Sci Technol ; 56(4): 2816-2826, 2022 02 15.
Article em En | MEDLINE | ID: mdl-35107268
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Purificação da Água / Aprendizado Profundo Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Purificação da Água / Aprendizado Profundo Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article