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CNN-BiLSTM Hybrid Neural Network with Attention Mechanism for Structural Nonlinear Model Updating

dc.contributor.authorDing, Ya-Jie
dc.contributor.authorWang, Zuo-Cai
dc.contributor.authorWang, Ye
dc.contributor.authorXin, Yu
dc.contributor.authorSun, Pei
dc.date.accessioned2026-08-20T21:21:59Z
dc.date.available2026-08-20T21:21:59Z
dc.date.copyright2026/03/12
dc.date.issued2026
dc.identifier.otherJBENF2.BEENG-7971.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314346
dc.description.abstractAbstract This paper proposes a hybrid neural network employing an attention mechanism (AM) strategy in nonlinear parameter identification for updating structural models based on dynamic response data, which integrates the characteristics of both a ...
dc.publisherAmerican Society of Civil Engineers
dc.titleCNN-BiLSTM Hybrid Neural Network with Attention Mechanism for Structural Nonlinear Model Updating
dc.typeJournal Article
dc.journal.volume31
dc.journal.issue5
dc.journal.titleJournal of Bridge Engineering
dc.identifier.doi10.1061/JBENF2.BEENG-7971
dc.journal.fristpage04026019-1
dc.journal.lastpage04026019-18
dc.page18
dc.treeJournal of Bridge Engineering:;2026:;Volume ( 031 ):;issue: 005
dc.contenttypeFulltext


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