Machine Learning–Based Source Identification in Sewer Networks-Reference-Cited by-同舟云学术

Machine Learning–Based Source Identification in Sewer Networks

Published:2023-08 Issue:8 Volume:149 Page:
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Salem Aly K.¹^ORCID,Abokifa Ahmed A.²^ORCID

Affiliation:

1. Ph.D. Student, Dept. of Civil, Materials, and Environmental Engineering, Univ. of Illinois Chicago, Chicago, IL 60607; Assistant Lecturer, Faculty of Engineering, Cairo Univ., Giza 12613, Egypt. ORCID:

2. Assistant Professor, Dept. of Civil, Materials, and Environmental Engineering, Univ. of Illinois Chicago, Chicago, IL 60607 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JWRMD5.WRENG-6050

Reference53 articles.

1. Towards Development of an Optimization Model to Identify Contamination Source in a Water Distribution Network

2. Prevalence of human pathogenic viruses in wastewater: A potential transmission risk as well as an effective tool for early outbreak detection for COVID-19

3. Optimal Placement of Water Quality Monitoring Stations in Sewer Systems: An Information Theory Approach

4. SWMM5 Toolkit Development for Pollution Source Identification in Sewer Systems

5. Illicit intrusion characterization in sewer systems

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