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

    Source: Journal of Bridge Engineering:;2026:;Volume ( 031 ):;issue: 005::page 04026019-1
    Author:
    Ding, Ya-Jie
    ,
    Wang, Zuo-Cai
    ,
    Wang, Ye
    ,
    Xin, Yu
    ,
    Sun, Pei
    DOI: 10.1061/JBENF2.BEENG-7971
    Publisher: American Society of Civil Engineers
    Abstract: Abstract 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 ...
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      CNN-BiLSTM Hybrid Neural Network with Attention Mechanism for Structural Nonlinear Model Updating

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314346
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    contributor authorDing, Ya-Jie
    contributor authorWang, Zuo-Cai
    contributor authorWang, Ye
    contributor authorXin, Yu
    contributor authorSun, Pei
    date accessioned2026-08-20T21:21:59Z
    date available2026-08-20T21:21:59Z
    date copyright2026/03/12
    date issued2026
    identifier otherJBENF2.BEENG-7971.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314346
    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 ...
    publisherAmerican Society of Civil Engineers
    titleCNN-BiLSTM Hybrid Neural Network with Attention Mechanism for Structural Nonlinear Model Updating
    typeJournal Article
    journal volume31
    journal issue5
    journal titleJournal of Bridge Engineering
    identifier doi10.1061/JBENF2.BEENG-7971
    journal fristpage04026019-1
    journal lastpage04026019-18
    page18
    treeJournal of Bridge Engineering:;2026:;Volume ( 031 ):;issue: 005
    contenttypeFulltext
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