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Research Articles

A methodology for leak detection in water distribution networks using graph theory and artificial neural network

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Pages 525-533 | Received 15 Feb 2020, Accepted 10 Jul 2020, Published online: 05 Aug 2020

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Shi Xiaoyu, Liu Zijing, Carlos Velazquez & Jia Haifeng. (2023) The role of graph-based methods in urban drainage networks (UDNs): review and directions for future. Urban Water Journal 0:0, pages 1-15.
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Michael Weyns, Ganjour Mazaev, Guido Vaes, Filip Vancoillie, Filip De Turck, Sofie Van Hoecke & Femke Ongenae. (2023) Leak localization in water distribution networks using GIS-Enhanced autoencoders. Urban Water Journal 20:7, pages 859-881.
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Articles from other publishers (12)

Hongfei Zhang, Zhaowei Ding, Liyue Zhou & Degang Wang. (2023) Particle Filtering SLAM algorithm for urban pipe leakage detection and localization. Wireless Networks.
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Mohammad Reza Shekofteh, Ehsan Yousefi-Khoshqalb & Kalyan R. Piratla. (2023) An Efficient Approach for Partitioning Water Distribution Networks Using Multi-Objective Optimization and Graph Theory. Water Resources Management 37:13, pages 5007-5022.
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Nikolaj T. Mücke, Prerna Pandey, Shashi Jain, Sander M. Bohté & Cornelis W. Oosterlee. (2023) A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning. Sensors 23:13, pages 6179.
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Puru Dutt Sharma, Srinivas Rallapalli & Naga Rajiv Lakkaniga. (2023) An innovative approach for predicting pandemic hotspots in complex wastewater networks using graph theory coupled with fuzzy logic. Stochastic Environmental Research and Risk Assessment.
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Brett Snider, Gareth Lewis, Albert Chen, Lydia Vamvakeridou & Dragan Savić. (2023) A flexible, leak crew focused localization model using a maximum coverage search area algorithm. IOP Conference Series: Earth and Environmental Science 1136:1, pages 012042.
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Luis Romero-Ben, Débora Alves, Joaquim Blesa, Gabriela Cembrano, Vicenç Puig & Eric Duviella. (2023) Leak detection and localization in water distribution networks: Review and perspective. Annual Reviews in Control 55, pages 392-419.
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T.H. Shabangu, Y. Ramam, J.A. Jordaan & K.B. Adedeji. (2022) Trends and Applications of Model-Driven Approach for Leak Detection in Water Supply Networks. Trends and Applications of Model-Driven Approach for Leak Detection in Water Supply Networks.
Maryam Kammoun, Amina KammounMohamed Abid. (2022) Leak Detection Methods in Water Distribution Networks: A Comparative Survey on Artificial Intelligence Applications. Journal of Pipeline Systems Engineering and Practice 13:3.
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Adrià Soldevila, Giacomo Boracchi, Manuel Roveri, Sebastian Tornil-Sin & Vicenç Puig. (2021) Leak detection and localization in water distribution networks by combining expert knowledge and data-driven models. Neural Computing and Applications 34:6, pages 4759-4779.
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Débora Alves, Joaquim Blesa, Eric Duviella & Lala Rajaoarisoa. (2022) Leak Detection in Water Distribution Networks Based on Water Demand Analysis. IFAC-PapersOnLine 55:6, pages 679-684.
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Marlon Jesús Ares-Milián, Marcos Quiñones-Grueiro, Cristina Verde & Orestes Llanes-Santiago. (2021) A Leak Zone Location Approach in Water Distribution Networks Combining Data-Driven and Model-Based Methods. Water 13:20, pages 2924.
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Marlon J. Ares-Milián, Marcos Quiñones-Grueiro, Carlos Cruz Corona & Orestes Llanes-Santiago. 2021. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications 340 350 .

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