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Risk-Based Water Pipe Failure Prediction through Machine Learning and Hydraulic Models

dc.contributor.authorKo, Taegon
dc.contributor.authorFarmani, Raziyeh
dc.contributor.authorKeedwell, Edward
dc.contributor.authorBeig Zali, Ramiz
dc.date.accessioned2026-08-20T21:05:53Z
dc.date.available2026-08-20T21:05:53Z
dc.date.copyright2025/07/03
dc.date.issued2025
dc.identifier.otherJWRMD5.WRENG-6958.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313945
dc.description.abstractAbstractFailures in water transmission lines (WTLs) can cause severe disruptions, high repair costs, and extensive damage to surrounding areas. The interest in proactive management through predictive methods as a way to mitigate these risks is growing. ...
dc.publisherAmerican Society of Civil Engineers
dc.titleRisk-Based Water Pipe Failure Prediction through Machine Learning and Hydraulic Models
dc.typeJournal Article
dc.journal.volume151
dc.journal.issue9
dc.journal.titleJournal of Water Resources Planning and Management
dc.identifier.doi10.1061/JWRMD5.WRENG-6958
dc.journal.fristpage04025038-1
dc.journal.lastpage04025038-15
dc.page15
dc.treeJournal of Water Resources Planning and Management:;2025:;Volume ( 151 ):;issue: 009
dc.contenttypeFulltext


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