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    Adaptive Analysis for Random Response of Wind–Vehicle–Bridge System Based on a Hybrid Deep-Learning Method

    Source: Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 002::page 04025133-1
    Author:
    Xu, Xinyu
    ,
    Zhu, Siyu
    ,
    Li, Yongle
    DOI: 10.1061/JCCEE5.CPENG-6297
    Publisher: American Society of Civil Engineers
    Abstract: AbstractA hybrid method for random response analysis of a wind–vehicle–bridge (WVB) system is presented. The method employs the gated recurrent unit (GRU) network to predict dynamic responses of the WVB system, enhanced by the integration of the sparrow ...
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      Adaptive Analysis for Random Response of Wind–Vehicle–Bridge System Based on a Hybrid Deep-Learning Method

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314371
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    contributor authorXu, Xinyu
    contributor authorZhu, Siyu
    contributor authorLi, Yongle
    date accessioned2026-08-20T21:23:05Z
    date available2026-08-20T21:23:05Z
    date copyright2025/11/17
    date issued2026
    identifier otherJCCEE5.CPENG-6297.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314371
    description abstractAbstractA hybrid method for random response analysis of a wind–vehicle–bridge (WVB) system is presented. The method employs the gated recurrent unit (GRU) network to predict dynamic responses of the WVB system, enhanced by the integration of the sparrow ...
    publisherAmerican Society of Civil Engineers
    titleAdaptive Analysis for Random Response of Wind–Vehicle–Bridge System Based on a Hybrid Deep-Learning Method
    typeJournal Article
    journal volume40
    journal issue2
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-6297
    journal fristpage04025133-1
    journal lastpage04025133-11
    page11
    treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 002
    contenttypeFulltext
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