Semi-supervised anomaly detection methods for leakage identification in water distribution networks: A comparative study
This study presents a comprehensive evaluation of 10 state of the art semi-supervised anomaly detection (AD) methods for leakage identification in water distribution networks (WDNs). The performances of the semi-supervised AD methods is evaluated on LeakDB, a benchmark consisting of independent leak...
Main Authors: | Hoese Michel Tornyeviadzi, Hadi Mohammed, Razak Seidu |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2023-12-01
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Series: | Machine Learning with Applications |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827023000543 |
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