Data‐mining methods predict chlorine residuals in premise plumbing using low‐cost sensors-Reference-Cited by-同舟云学术

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Data‐mining methods predict chlorine residuals in premise plumbing using low‐cost sensors

Published:2021-01 Issue:1 Volume:3 Page:
ISSN:2577-8161
Container-title:AWWA Water Science
language:en
Short-container-title:AWWA Water Science

Author:

Saetta Daniella¹²^ORCID,Richard Rain¹²^ORCID,Leyva Carlos³^ORCID,Westerhoff Paul²^ORCID,Boyer Treavor H.¹²^ORCID

Affiliation:

1. Swette Center for Environmental Biotechnology The Biodesign Institute at Arizona State University Tempe Arizona

2. School of Sustainable Engineering and the Built Environment (SSEBE) Arizona State University Tempe Arizona

3. ASU Future H₂O Office of Knowledge Enterprise Development Arizona State University Tempe Arizona

Funder

Arizona State University

Drexel University

National Science Foundation

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aws2.1214

Reference33 articles.

1. Microbial ecology of drinking water distribution systems

2. Hands-On Machine Learning with R

3. Effect of chlorine on corrosion in Drinking Water Systems

4. Predicting disinfection by-product formation potential in water

5. Models for predicting disinfection byproduct (DBP) formation in drinking waters: A chronological review

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sorption-based atmospheric water harvesting for continuous water production in the built environment: Assessment of water yield and quality;Water Research;2024-11

2. High resolution data visualization and machine learning prediction of free chlorine residual in a green building water system;Water Research X;2024-09

3. Efficacy of chlorine-based disinfectants to control Legionella within premise plumbing systems;Water Research;2024-08

4. Can free chlorine residuals entering building plumbing systems really be maintained to prevent microbial growth?;Science of The Total Environment;2024-08

5. A point-of-use drinking water quality dataset from fieldwork in Detroit, Michigan;Scientific Data;2024-05-03

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