Machine learning models with potential application to predict source water quality for treatment purposes: a critical review-Reference-Cited by-同舟云学术

Machine learning models with potential application to predict source water quality for treatment purposes: a critical review

Published:2022-09-06 Issue:1 Volume:11 Page:118-147
ISSN:2162-2515
Container-title:Environmental Technology Reviews
language:en
Short-container-title:Environmental Technology Reviews

Author:

Ortiz-Lopez Christian¹^ORCID,Bouchard Christian¹,Rodriguez Manuel¹²^ORCID

Affiliation:

1. Centre de recherche en aménagement et développement, Université Laval, Québec, Canada

2. École supérieure d’aménagement du territoire et de développement régional, Université Laval, Québec, Canada

Funder

Natural Sciences and Engineering Research Council of Canada

NSERC

Publisher

Informa UK Limited

Subject

Pollution,Waste Management and Disposal,Water Science and Technology,Environmental Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/21622515.2022.2118084

Reference91 articles.

1. Health Canada. Guidance for providing safe drinking water in areas of federal jurisdiction; 2013. Available from: https://www.canada.ca/content/dam/canada/health-canada/migration/healthy-canadians/publications/healthy-living-vie-saine/water-federal-eau/alt/water-federal-eau-eng.pdf.

2. World Health Organization. Guidelines for drinking-water quality: fourth edition incorporating the first addendum; 2017.

3. Health Canada. From source to tap the multi-barrier approach to safe drinking water; 2002. Available from: www.ccme.ca.

4. Water Quality

5. Crittenden JC, Trussell RR, Hand DW, et al. MWH’s water treatment – principles and design. 3rd ed.; 2012.

Cited by 7 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. Predicting groundwater phosphate levels in coastal multi-aquifers: A geostatistical and data-driven approach;Science of The Total Environment;2024-11

2. Ensemble machine learning using hydrometeorological information to improve modeling of quality parameter of raw water supplying treatment plants;Journal of Environmental Management;2024-06

3. Machine Learning and AI-Driven Water Quality Monitoring and Treatment;E3S Web of Conferences;2024

4. Prediction and Analysis of Water Quality Using Machine Learning Techniques;Lecture Notes in Networks and Systems;2024

5. Practical application of machine learning for organic matter and harmful algal blooms in freshwater systems: A review;Critical Reviews in Environmental Science and Technology;2023-11-29