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1D–CNN with SMOTE for Acoustic Detection and Classification of Structural Defects in Municipal Sewage Pipelines: Addressing Imbalanced Data Set and High Sewage Level Challenges

dc.contributor.authorWang, Xiaocen
dc.contributor.authorCui, Nuo
dc.contributor.authorFan, Jinpeng
dc.contributor.authorGu, Yijie
dc.contributor.authorZhang, Jun
dc.contributor.authorLiu, Nannan
dc.contributor.authorAn, Yang
dc.contributor.authorHu, Xinyue
dc.contributor.authorQu, Zhigang
dc.date.accessioned2026-08-20T12:06:31Z
dc.date.available2026-08-20T12:06:31Z
dc.date.copyright2026/02/19
dc.date.issued2026
dc.identifier.otherJPSEA2.PSENG-1962.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313107
dc.description.abstractAbstractThe rapid growth of urbanization has led to an increase in the size of sewage pipelines. However, due to factors such as environmental conditions, misuse, and age, many pipelines are defective to varying degrees and thus impact the ecosystem. ...
dc.publisherAmerican Society of Civil Engineers
dc.title1D–CNN with SMOTE for Acoustic Detection and Classification of Structural Defects in Municipal Sewage Pipelines: Addressing Imbalanced Data Set and High Sewage Level Challenges
dc.typeJournal Article
dc.journal.volume17
dc.journal.issue2
dc.journal.titleJournal of Pipeline Systems Engineering and Practice
dc.identifier.doi10.1061/JPSEA2.PSENG-1962
dc.journal.fristpage04026016-1
dc.journal.lastpage04026016-12
dc.page12
dc.treeJournal of Pipeline Systems Engineering and Practice:;2026:;Volume ( 017 ):;issue: 002
dc.contenttypeFulltext


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