Coagulant dosage determination using deep learning-based graph attention multivariate time series forecasting model.

Lin, Subin; Kim, Jiwoong; Hua, Chuanbo; Park, Mi-Hyun; Kang, Seoktae

Lin, Subin; Kim, Jiwoong; Hua, Chuanbo; Park, Mi-Hyun; Kang, Seoktae.

Afiliación

Lin S; Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Korea.
Kim J; Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Korea; Korea water resources corporation (K-water), 200 Sintanjin-ro, Daedeok-gu, Deajeon, 34350, Korea.
Hua C; Industrial and System Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Korea.
Park MH; Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Korea. Electronic address: mpark.kaist@gmail.com.
Kang S; Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Korea. Electronic address: stkang@kaist.ac.kr.

Water Res ; 232: 119665, 2023 Apr 01.

Article en En | MEDLINE | ID: mdl-36739659

Asunto(s)

Aprendizaje Profundo; Purificación del Agua; Factores de Tiempo; Aprendizaje Automático; Purificación del Agua/métodos; Tiempo (Meteorología); Predicción

Palabras clave

Attention-based mechanism; Big data; Coagulant; Deep learning; Prediction model; Time series

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Purificación del Agua / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: Water Res Año: 2023 Tipo del documento: Article

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