Leakage detection and localization on water transportation pipelines: a multi-label classification approach

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dc.contributor.authorKayaalp, Fatih
dc.contributor.authorZengin, Ahmet
dc.contributor.authorKara, Resul
dc.contributor.authorZavrak, Sultan
dc.date.accessioned2020-04-30T23:18:53Z
dc.date.available2020-04-30T23:18:53Z
dc.date.issued2017
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionZavrak/0000-0001-6950-8927; Kara, Resul/0000-0001-8902-6837; Kayaalp, Fatih/0000-0002-8752-3335en_US
dc.descriptionWOS: 000426865100007en_US
dc.description.abstractOne of the main problems of water transportation pipelines is leak which can cause water resources loss, possible human injuries, and damages to the environment. There are many studies in the literature focusing on detection and localization of leaks in the water pipeline systems. In this study, we have designed a wireless sensor network-based real-time monitoring system to detect and locate the leaks on multiple positions on water pipelines by using pressure data. At first, the pressure data are collected from wireless pressure sensor nodes. After that, unlike from the previous works in the literature, both the detection and localization of leakages are carried out by using multi-label learning methods. We have used three multi-label classification methods which are RAkELd, BRkNN, and BR with SVM. After the evaluation and comparison of the methods with each other, we observe that the RAkELd method performs best on almost all measures with the accuracy ratio of 98%. As a result, multi-label classification methods can be used on the detection and localization of the leaks in the pipeline systems successfully.en_US
dc.identifier.doi10.1007/s00521-017-2872-4en_US
dc.identifier.endpage2914en_US
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue10en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2905en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-017-2872-4
dc.identifier.urihttps://hdl.handle.net/20.500.12684/3569
dc.identifier.volume28en_US
dc.identifier.wosWOS:000426865100007en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer London Ltden_US
dc.relation.ispartofNeural Computing & Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectWireless sensor networksen_US
dc.subjectWater leakage detectionen_US
dc.subjectMulti-label classificationen_US
dc.subjectLeak localizationen_US
dc.subjectRAkEL(d)en_US
dc.titleLeakage detection and localization on water transportation pipelines: a multi-label classification approachen_US
dc.typeArticleen_US

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