Leveraging One-Dimensional Deep Learning for Robust Leak Detection in Water Distribution Systems Using Acceleration Data

dc.contributor.author	Dunphy, Kyle
dc.contributor.author	Agarwal, Harsha
dc.contributor.author	Sadhu, Ayan
dc.date.accessioned	2026-08-20T12:05:01Z
dc.date.available	2026-08-20T12:05:01Z
dc.date.copyright	2025/07/02
dc.date.issued	2025
dc.identifier.other	JPSEA2.PSENG-1861.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4313074
dc.description.abstract	AbstractOperational water distribution networks (WDNs) are of paramount importance to the many facets of socioeconomic demands that are required by global society. Infrastructure degradation and failures in the form of leak defects and catastrophic ...
dc.publisher	American Society of Civil Engineers
dc.title	Leveraging One-Dimensional Deep Learning for Robust Leak Detection in Water Distribution Systems Using Acceleration Data
dc.type	Journal Article
dc.journal.volume	16
dc.journal.issue	4
dc.journal.title	Journal of Pipeline Systems Engineering and Practice
dc.identifier.doi	10.1061/JPSEA2.PSENG-1861
dc.journal.fristpage	04025066-1
dc.journal.lastpage	04025066-25
dc.page	25
dc.tree	Journal of Pipeline Systems Engineering and Practice:;2025:;Volume ( 016 ):;issue: 004
dc.contenttype	Fulltext