Partitioning Leakage Detection in Water Distribution Systems: A Specialized Deep Learning Framework Enhanced by Spatial–Temporal Graph Convolutional Networks-Reference-Cited by-同舟云学术

Partitioning Leakage Detection in Water Distribution Systems: A Specialized Deep Learning Framework Enhanced by Spatial–Temporal Graph Convolutional Networks

Published:2024-07-31 Issue:8 Volume:4 Page:3453-3463
ISSN:2690-0637
Container-title:ACS ES&T Water
language:en
Short-container-title:ACS EST Water

Author:

Mu Tianwei¹^ORCID,Zhang Chunzheng¹,Huang Manhong²^ORCID,Ning Baokuan¹,Wang Junxiang¹

Affiliation:

1. School of Architecture & Civil Engineering, Shenyang University of Technology, Shenyang 110023, China

2. College of Environmental Science and Engineering, State Environmental Protection Engineering Center for Pollution Treatment and Control in Textile Industry, Donghua University, Shanghai 201620, China

Funder

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsestwater.4c00285

Reference36 articles.

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2. Prediction of stress concentration factor of corrosion pits on buried pipes by least squares support vector machine

3. Numerical Simulation of Pressure Transients in Water Supply Networks as Applicable to Critical Water Pipe Asset Management

4. Merging Fluid Transient Waves and Artificial Neural Networks for Burst Detection and Identification in Pipelines

5. Adaptive Multipopulation Evolutionary Algorithm for Contamination Source Identification in Water Distribution Systems