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High resolution data visualization and machine learning prediction of free chlorine residual in a green building water system.

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第一作者： S,Wei

第一单位： School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281, United States.

作者： S,Wei ^[1] ; R,Richard ^[2] ; D,Hogue ^[1] ; I,Mondal ^[3] ; T,Xu ^[1] ; T H,Boyer ^[1] ; K A,Hamilton ^[3]

作者单位： School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281, United States. ^[1] Wilson & Company Engineers, United States. ^[2] School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281, United States.;Biodesign Center for Environmental Health Engineering, Arizona State University, Tempe, AZ 85281, United States. ^[3]

关键词 Artificial intelligence (AI)Machine learning (ML)Opportunistic pathogens Premise plumbing

DOI 10.1016/j.wroa.2024.100244

PMID 39188328

发布时间 2024-08-28

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Water research X

2024年24卷

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Water research X

2024年24卷

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High resolution data visualization and machine learning prediction of free chlorine residual in a green building water system.

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High resolution data visualization and machine learning prediction of free chlorine residual in a green building water system.

Water research X

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Water research X

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