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Prediction model and application of machine learning for supersaturated total dissolved gas generation in high dam discharge.
Wang, Zhenhua; Feng, Jingjie; Liang, Mingyu; Wu, Zhonghang; Li, Ran; Chen, Zhuo; Liang, Ruifeng.
  • Wang Z; State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
  • Feng J; State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, Sichuan, 610065, China. Electronic address: fengjingjie@scu.edu.cn.
  • Liang M; Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Wu Z; State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
  • Li R; State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
  • Chen Z; State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
  • Liang R; State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, Sichuan, 610065, China.
Water Res ; 220: 118682, 2022 Jul 15.
Article en En | MEDLINE | ID: mdl-35661511
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Movimientos del Agua / Gases Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2022 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Movimientos del Agua / Gases Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2022 Tipo del documento: Article