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Attention-Based Encoder for Online Data Anomaly Classification in Multivariate Time Series

dc.contributor.authorYang, Qun
dc.contributor.authorYu, Xiao
dc.contributor.authorFu, Yuguang
dc.date.accessioned2026-08-20T21:26:08Z
dc.date.available2026-08-20T21:26:08Z
dc.date.copyright2025/08/08
dc.date.issued2025
dc.identifier.otherJCCEE5.CPENG-6842.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314447
dc.description.abstractAbstractData collected from low-cost sensors in structural health monitoring (SHM) often contain anomalies, leading to misinterpretations of subsequent structural condition assessment. Therefore, the classification model is required to identify various ...
dc.publisherAmerican Society of Civil Engineers
dc.titleAttention-Based Encoder for Online Data Anomaly Classification in Multivariate Time Series
dc.typeJournal Article
dc.journal.volume39
dc.journal.issue6
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-6842
dc.journal.fristpage04025094-1
dc.journal.lastpage04025094-14
dc.page14
dc.treeJournal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 006
dc.contenttypeFulltext


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