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Lake eutrophication prediction based on improved MIMO-DD-3Q Learning.
Wang, Li; Ning, Chaoran; Wang, Xiaoyi; Xu, Jiping; Zhao, Zhiyao; Yu, Jiabin; Zhang, Huiyan; Sun, Qian; Bai, Yuting; Jin, Xuebo; Tang, Qianhui.
Afiliación
  • Wang L; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
  • Ning C; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
  • Wang X; Beijing Institute of Fashion Technology, Beijing, China.
  • Xu J; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
  • Zhao Z; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
  • Yu J; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
  • Zhang H; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
  • Sun Q; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
  • Bai Y; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
  • Jin X; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
  • Tang Q; Beijing Laboratory for Intelligent Environmental Protection, School of Artificial Intelligence, Beijing Technology and Business University, Beijing, China.
PLoS One ; 18(11): e0294278, 2023.
Article en En | MEDLINE | ID: mdl-37963129
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Lagos / Monitoreo del Ambiente País/Región como asunto: Asia Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Lagos / Monitoreo del Ambiente País/Región como asunto: Asia Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos