Sensor Placement Optimization in Sewer Networks: Machine Learning–Based Source Identification Approach-Reference-Cited by-同舟云学术

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Sensor Placement Optimization in Sewer Networks: Machine Learning–Based Source Identification Approach

Published:2024-11 Issue:11 Volume:150 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)

Link

https://ascelibrary.org/doi/pdf/10.1061/JWRMD5.WRENG-6430

Reference37 articles.

1. SENSOR PLACEMENT STRATEGIES FOR CONTAMINATION IDENTIFICATION IN WATER DISTRIBUTION NETWORKS: A REVIEW

2. Multi-objective Coverage-based ACO Model for Quality Monitoring in Large Water Networks

3. Optimal Design of Sensor Placement in Water Distribution Networks

4. Greedy Algorithms for Sensor Location in Sewer Systems

5. Evaluation of Different Formulations to Optimally Locate Sensors in Sewer Systems

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