Multiobjective Wrapper Sampling Design for Leak Detection of Pipe Networks Based on Machine Learning and Transient Methods-Reference-Cited by-同舟云学术

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Multiobjective Wrapper Sampling Design for Leak Detection of Pipe Networks Based on Machine Learning and Transient Methods

Published:2023-02 Issue:2 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:

Ayati Amir Houshang¹^ORCID,Haghighi Ali²^ORCID

Affiliation:

1. Lecturer, Faculty of Civil Engineering and Architecture, Shahid Chamran Univ. of Ahvaz, Ahvaz 6135783151, Iran (corresponding author). ORCID: .

2. Professor, Faculty of Civil Engineering and Architecture, Shahid Chamran Univ. of Ahvaz, Ahvaz 6135783151, Iran. 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-5620

Reference78 articles.

1. Machine Learning–Assisted Model for Leak Detection in Water Distribution Networks Using Hydraulic Transient Flows

2. Machine learning approach to transient-based leak detection of pressurized pipelines: Classification vs Regression

3. Statistical review of major standpoints in hydraulic transient-based leak detection;Ayati A. H.;J. Hydraul. Struct.,2019

4. Wavelet and Cepstrum Analyses of Leaks in Pipe Networks

5. Berry J. W. W. E. Hart C. A. Phillips and J.-P. Watson. 2008. “A facility location approach to sensor placement optimization.” In Proc. Water Distribution Systems Analysis Symp. 2006 1–4. Reston VA: ASCE. https://doi.org/10.1061/40941(247)111.

Cited by 4 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. Calibration of Frequency-Dependent Wave Speed and Attenuation in Water Pipes Using a Dual-Sensor and Paired-IRF Approach;Journal of Water Resources Planning and Management;2024-11

2. Sinkhole Risk-Based Sensor Placement for Leakage Localization in Water Distribution Networks with a Data-Driven Approach;Sustainability;2024-06-20

3. Water depth prediction in combined sewer networks, application of generative adversarial networks;Discover Applied Sciences;2024-03-11

4. Water distribution pipe lifespans: Predicting when to repair the pipes in municipal water distribution networks using machine learning techniques;PLOS Water;2024-01-09

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