Leak Detection in Water Supply Network Using a Data-Driven Improved Graph Convolutional Network-Reference-Cited by-同舟云学术

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Leak Detection in Water Supply Network Using a Data-Driven Improved Graph Convolutional Network

Published:2023 Issue: Volume:11 Page:117240-117249
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Chen Suisheng¹^ORCID,Wang Yun²^ORCID,Zhang Wei¹,Zhang Hairong³,He Yuchen³^ORCID

Affiliation:

1. Hangzhou Vocational & Technical College, Fair Friend Institute of Intelligent Manufacturing, Hangzhou, China

2. Mechanical and Electrical Engineering Department, Zhejiang Tongji Vocational College of Science and Technology, Hangzhou, China

3. Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province, China Jiliang University, Hangzhou, China

Funder

Hangzhou Key Scientific Research Program of China

Fundamental Research Funds for the Provincial Universities of Zhejiang

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10290897.pdf?arnumber=10290897

Reference33 articles.

1. Leakage detection in water distribution networks via 1D CNN deep autoencoder for multivariate SCADA data

2. An Accurate Leakage Localization Method for Water Supply Network Based on Deep Learning Network

3. Development of Leakage Detection Model and Its Application for Water Distribution Networks Using RNN-LSTM

4. A Pipeline Leak Detection and Localization Approach Based on Ensemble TL1DCNN

5. Framework for Modeling Lead in Premise Plumbing Systems Using EPANET

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Partitioning Leakage Detection in Water Distribution Systems: A Specialized Deep Learning Framework Enhanced by Spatial–Temporal Graph Convolutional Networks;ACS ES&T Water;2024-07-31

2. Intelligent identification method for pipeline leakage based on GPR time–frequency features and deep learning;AQUA — Water Infrastructure, Ecosystems and Society;2024-06-25

3. Separation Anomaly Distribution with a Triplet Network for Leakage Detection;Journal of Digital Contents Society;2024-05-31

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