Predicting unregulated disinfection by-products in water distribution networks using generalized regression neural networks-Reference-Cited by-同舟云学术

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Predicting unregulated disinfection by-products in water distribution networks using generalized regression neural networks

Published:2021-05-19 Issue:9 Volume:18 Page:711-724
ISSN:1573-062X
Container-title:Urban Water Journal
language:en
Short-container-title:Urban Water Journal

Author:

Mian Haroon R.¹^ORCID,Hu Guangji¹,Hewage Kasun¹,Rodriguez Manuel J.²,Sadiq Rehan¹

Affiliation:

1. School of Engineering, University of British Columbia Okanagan, 3333 University Way, Kelowna, Canada

2. École Supérieure D’aménagement du Territoire et Développement Régional (ESAD), 2325, allée des Bibliothèque Université Laval, Québec City, Canada

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/1573062X.2021.1925707

Reference66 articles.

1. Predictive model for disinfection by-product in Alexandria drinking water, northern west of Egypt

2. State-of-the-art in artificial neural network applications: A survey

3. Applications of General Regression Neural Networks in Dynamic Systems

4. Evaluation of conventional drinking water treatment plant efficiency according to water quality index and health risk assessment

5. Disinfection By-Products Formation Potential Along the Melendiz River, Turkey; Associated Water Quality Parameters and Non-Linear Prediction Model

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1. Application of artificial intelligence in (waste)water disinfection: Emphasizing the regulation of disinfection by-products formation and residues prediction;Water Research;2024-04

2. The combination of multiple linear regression and adaptive neuro-fuzzy inference system can accurately predict trihalomethane levels in tap water with fewer water quality parameters;Science of The Total Environment;2023-10

3. Appraisal of machine learning techniques for predicting emerging disinfection byproducts in small water distribution networks;Journal of Hazardous Materials;2023-03

4. Predicting THM Formation and Revealing Its Contributors in Drinking Water Treatment Using Machine Learning;ACS ES&T Water;2023-02-24

5. Digital water: artificial intelligence and soft computing applications for drinking water quality assessment;Clean Technologies and Environmental Policy;2023-02-02

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