Application of Neural Network–Based Modeling for Leak Localization in Water Mains-Reference-Cited by-同舟云学术

Application of Neural Network–Based Modeling for Leak Localization in Water Mains

Published:2022-11 Issue:4 Volume:13 Page:
ISSN:1949-1190
Container-title:Journal of Pipeline Systems Engineering and Practice
language:en
Short-container-title:J. Pipeline Syst. Eng. Pract.

Author:

Momeni Ahmad¹^ORCID,Piratla Kalyan R.²^ORCID,Chalil Madathil Kapil³

Affiliation:

1. Ph.D. Candidate, Glenn Dept. of Civil Engineering, Clemson Univ., Clemson, SC 29634 (corresponding author). ORCID: .

2. Liles Associate Professor, Glenn Dept. of Civil Engineering, Clemson Univ., Clemson, SC 29634. ORCID: .

3. Wilfred P. and Helen S. Tiencken Associate Professor of Civil and Industrial Engineering, Glenn Dept. of Civil Engineering, Clemson Univ., Clemson, SC 29634.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29PS.1949-1204.0000674

Reference37 articles.

1. Towards Achieving a Reliable Leakage Detection and Localization Algorithm for Application in Water Piping Networks: An Overview

2. Infrastructure Management: Integrated AHP/ANN Model to Evaluate Municipal Water Mains’ Performance

3. Design and development of a fuzzy credibility-based reverse logistics network with buyback offers: A case study;Amirdadi M.;Waste Manage. Res.,2021

4. A Leak Zone Location Approach in Water Distribution Networks Combining Data-Driven and Model-Based Methods

5. Leak detection in water distribution networks: an introductory overview

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