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

    Source: Journal of Pipeline Systems Engineering and Practice:;2025:;Volume ( 016 ):;issue: 004::page 04025066-1
    Author:
    Dunphy, Kyle
    ,
    Agarwal, Harsha
    ,
    Sadhu, Ayan
    DOI: 10.1061/JPSEA2.PSENG-1861
    Publisher: American Society of Civil Engineers
    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 ...
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      Leveraging One-Dimensional Deep Learning for Robust Leak Detection in Water Distribution Systems Using Acceleration Data

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4313074
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    contributor authorDunphy, Kyle
    contributor authorAgarwal, Harsha
    contributor authorSadhu, Ayan
    date accessioned2026-08-20T12:05:01Z
    date available2026-08-20T12:05:01Z
    date copyright2025/07/02
    date issued2025
    identifier otherJPSEA2.PSENG-1861.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313074
    description abstractAbstractOperational 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 ...
    publisherAmerican Society of Civil Engineers
    titleLeveraging One-Dimensional Deep Learning for Robust Leak Detection in Water Distribution Systems Using Acceleration Data
    typeJournal Article
    journal volume16
    journal issue4
    journal titleJournal of Pipeline Systems Engineering and Practice
    identifier doi10.1061/JPSEA2.PSENG-1861
    journal fristpage04025066-1
    journal lastpage04025066-25
    page25
    treeJournal of Pipeline Systems Engineering and Practice:;2025:;Volume ( 016 ):;issue: 004
    contenttypeFulltext
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