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dc.contributor.authorWang, Chang
dc.contributor.authorLong, Zhihong
dc.contributor.authorLin, Sen
dc.contributor.authorZhu, Zhu
dc.contributor.authorShao, Yu
dc.contributor.authorYu, Tingchao
dc.date.accessioned2026-08-20T21:05:56Z
dc.date.available2026-08-20T21:05:56Z
dc.date.copyright2025/12/17
dc.date.issued2026
dc.identifier.otherJWRMD5.WRENG-6967.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313946
dc.description.abstractAbstractTo ensure water supply safety and reduce environmental impact, it is essential to conduct failure modeling on water distribution networks (WDNs) to prevent pipe failures. However, the limited and imbalanced pipe break data in small and medium-...Practical ApplicationsDeep learning algorithms have emerged as powerful tools for predicting failures in water mains, but their effectiveness hinges on access to large volumes of failed pipe data from water distribution networks. However, small and medium-...
dc.publisherAmerican Society of Civil Engineers
dc.titleFailure Modeling of Small and Medium-Sized Water Distribution Networks Based on a Hybrid Ranking Model
dc.typeJournal Article
dc.journal.volume152
dc.journal.issue3
dc.journal.titleJournal of Water Resources Planning and Management
dc.identifier.doi10.1061/JWRMD5.WRENG-6967
dc.journal.fristpage04025076-1
dc.journal.lastpage04025076-12
dc.page12
dc.treeJournal of Water Resources Planning and Management:;2026:;Volume ( 152 ):;issue: 003
dc.contenttypeFulltext


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