Coupling Machine Learning and Agent-Based Modeling to Characterize Contamination Sources in Water Distribution Systems for Changing Demand Regimes-Reference-Cited by-同舟云学术

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Coupling Machine Learning and Agent-Based Modeling to Characterize Contamination Sources in Water Distribution Systems for Changing Demand Regimes

Published:2023-05-18 Issue: Volume: Page:
ISSN:
Container-title:World Environmental and Water Resources Congress 2023
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Author:

Berglund Emily¹²³⁴,Vizanko Brent¹²³⁴,Kadinski Leonid¹²³⁴,Ostfeld Avi¹²³⁴

Affiliation:

1. Professor, Dept. of Civil, Construction, and Environmental Engineering, North Carolina State Univ., Raleigh, NC.

2. Ph.D. Student, Dept. of Civil, Construction, and Environmental Engineering, North Carolina State Univ., Raleigh, NC.

3. Postdoctoral Fellow, Faculty of Civil and Environmental Engineering, Technion–Israel Institute of Technology, Haifa, Israel.

4. Professor, Faculty of Civil and Environmental Engineering, Technion–Israel Institute of Technology, Haifa, Israel.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784484852.082

Reference21 articles.

1. Water and Wastewater Systems and Utilities: Challenges and Opportunities during the COVID-19 Pandemic

2. Effects of the COVID-19 Pandemic on Water Utility Operations and Vulnerability

3. Brumbelow K. Torres J. Guikema S. Bristow E. and Kanta L. (2007). “Virtual cities for water distribution and infrastructure system research.” Proceedings of the 2007 World Environmental and Water Resources Congress ASCE Reston VA.

4. COVID-19 and water demand: A review of literature and research evidence;Cahill J.;WIREs Water,2022

5. A multi-hazard framework for spatial-temporal impact analysis

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