Importance of secondary decomposition in the accurate prediction of daily-scale ozone pollution by machine learning.

Du, Xinyue; Yuan, Zibing; Huang, Daojian; Ma, Wei; Yang, Jun; Mo, Jianbin

Du, Xinyue; Yuan, Zibing; Huang, Daojian; Ma, Wei; Yang, Jun; Mo, Jianbin.

Afiliación

Du X; School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
Yuan Z; School of Environment and Energy, South China University of Technology, Guangzhou 510006, China. Electronic address: zibing@scut.edu.cn.
Huang D; South China Institute of Environmental Sciences, Ministry of Ecology and Environment of China, Guangzhou 510655, China. Electronic address: huangdaojian@scies.org.
Ma W; School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
Yang J; School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
Mo J; School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.

Sci Total Environ ; 904: 166963, 2023 Dec 15.

Article en En | MEDLINE | ID: mdl-37696411

Palabras clave

MDA8; Machine learning; Ozone; Pearl River Delta; Secondary decomposition

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Total Environ Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos

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