Comparative analysis of surface water quality prediction performance and identification of key water parameters using different machine learning models based on big data.

Chen, Kangyang; Chen, Hexia; Zhou, Chuanlong; Huang, Yichao; Qi, Xiangyang; Shen, Ruqin; Liu, Fengrui; Zuo, Min; Zou, Xinyi; Wang, Jinfeng; Zhang, Yan; Chen, Da; Chen, Xingguo; Deng, Yongfeng; Ren, Hongqiang

Chen, Kangyang; Chen, Hexia; Zhou, Chuanlong; Huang, Yichao; Qi, Xiangyang; Shen, Ruqin; Liu, Fengrui; Zuo, Min; Zou, Xinyi; Wang, Jinfeng; Zhang, Yan; Chen, Da; Chen, Xingguo; Deng, Yongfeng; Ren, Hongqiang.

Afiliação

Chen K; Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, China.
Chen H; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, 510632, China.
Zhou C; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, 510632, China.
Huang Y; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, 510632, China.
Qi X; Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, China.
Shen R; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, 510632, China; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjin
Liu F; College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI, 48109, USA.
Zuo M; National Engineering Laboratory for Agri-product Quality Traceability, Beijing Technology and Business University, Beijing, Beijing, 100048, China.
Zou X; Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, China.
Wang J; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, Jiangsu, 210023, China.
Zhang Y; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, Jiangsu, 210023, China.
Chen D; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, 510632, China.
Chen X; Jiangsu Key Laboratory of Big Data Security & Intelligent Processing, Nanjing University of Posts and Telecommunications, Nanjing, China; State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, 210023, China. Electronic address: chenxg@njupt.edu.cn.
Deng Y; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou, Guangdong, 510632, China; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjin
Ren H; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, Jiangsu, 210023, China.

Water Res ; 171: 115454, 2020 Mar 15.

Article em En | MEDLINE | ID: mdl-31918388

Assuntos

Qualidade da Água; Água; Big Data; China; Aprendizado de Máquina

Palavras-chave

Deep cascade forest; Ensemble methods; Machine learning models; The key water parameters; Water quality prediction

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Qualidade da Água / Água Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies País/Região como assunto: Asia Idioma: En Revista: Water Res Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

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