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Knowledge extraction of sonophotocatalytic treatment for acid blue 113 dye removal by artificial neural networks.
Reddy, B S; Maurya, A K; Narayana, P L; Pasha, S K Khadheer; Reddy, M R; Hatshan, Mohammad Rafe; Darwish, Noura M; Kori, S A; Cho, Kwon-Koo; Reddy, N S.
Afiliação
  • Reddy BS; Department of Materials Engineering and Convergence Technology & RIGET, Gyeongsang National University, Jinju, 52828, South Korea.
  • Maurya AK; Virtual Materials Lab, School of Materials Science and Engineering, Engineering Research Institute, Gyeongsang National University, Jinju, 52828, South Korea.
  • Narayana PL; Virtual Materials Lab, School of Materials Science and Engineering, Engineering Research Institute, Gyeongsang National University, Jinju, 52828, South Korea.
  • Pasha SKK; Department of Physics, Vellore Institute of Technology (Amaravati Campus), Amaravati, 522501, Guntur, Andhra Pradesh, India.
  • Reddy MR; Computer Science and Engineering. Srinivasa Ramanujan Institute of Technology, Anantapur, 515701, India.
  • Hatshan MR; Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia.
  • Darwish NM; Faculty of Science Ain Shams University, Biochemistry Department, Abbasaya, P.O. Box., 11566, Cairo, Egypt; Ministry of Health Laboratories, Tanta, Egypt.
  • Kori SA; Central University of Andra Pradesh (CUAP), Anantapuram, Andra Pradesh, 515002, India.
  • Cho KK; Department of Materials Engineering and Convergence Technology & RIGET, Gyeongsang National University, Jinju, 52828, South Korea.
  • Reddy NS; Virtual Materials Lab, School of Materials Science and Engineering, Engineering Research Institute, Gyeongsang National University, Jinju, 52828, South Korea. Electronic address: nsreddy@gnu.ac.kr.
Environ Res ; 204(Pt D): 112359, 2022 03.
Article em En | MEDLINE | ID: mdl-34774834
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Compostos Azo / Redes Neurais de Computação Tipo de estudo: Prognostic_studies Idioma: En Revista: Environ Res Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Coréia do Sul
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Compostos Azo / Redes Neurais de Computação Tipo de estudo: Prognostic_studies Idioma: En Revista: Environ Res Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Coréia do Sul