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dc.contributor.authorBlázquez-García, A.
dc.contributor.authorConde, A.
dc.contributor.authorMori, U. 
dc.contributor.authorLozano, J.A.
dc.description.abstractLeaks in water distribution networks cause a loss of water that needs to be com- pensated to ensure a continuous supply for all customers. This compensation is achieved by increasing the flow of the network, which entails an undesirable economical expense as well as negative consequences for the environment. For these reasons, detecting and fixing leaks is a relevant task for water distribution companies. This paper proposes a water leak detection method based on a self- supervised classification of flow time series. The aim is to detect the leaks in the network, providing a low false positive rate. The proposed method is applied to two water distribution networks and compared to two other methods in the literature, obtaining the best balance between the number of false positives and detected leaks.en_US
dc.description.sponsorshipIT1244-19 PID2019-104966GB-I00en_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.subjectleak detectionen_US
dc.subjectanomaly detectionen_US
dc.subjecttime seriesen_US
dc.subjectself-supervised classificationen_US
dc.titleWater leak detection using self-supervised time series classificationen_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/Gobierno Vasco/BERC/BERC.2018-2021en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/Gobierno Vasco/ELKARTEKen_US
dc.journal.titleInformation Sciencesen_US

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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España