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    Stiffness-Embedded GNN Model for Structural Component Importance Analysis

    Source: Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003::page 04026003-1
    Author:
    Ji, Xiaolong
    ,
    Wei, Kedong
    ,
    Chen, Zhaohui
    ,
    Liu, Yu
    DOI: 10.1061/JCCEE5.CPENG-6920
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThis study proposes a framework for evaluating structural component importance (SCI) in framed structures by combining graph neural networks (GNNs) with an energy-based method (EBM). EBM provides an accurate and comprehensive training data set ...
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      Stiffness-Embedded GNN Model for Structural Component Importance Analysis

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314455
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    contributor authorJi, Xiaolong
    contributor authorWei, Kedong
    contributor authorChen, Zhaohui
    contributor authorLiu, Yu
    date accessioned2026-08-20T21:26:26Z
    date available2026-08-20T21:26:26Z
    date copyright2026/01/21
    date issued2026
    identifier otherJCCEE5.CPENG-6920.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314455
    description abstractAbstractThis study proposes a framework for evaluating structural component importance (SCI) in framed structures by combining graph neural networks (GNNs) with an energy-based method (EBM). EBM provides an accurate and comprehensive training data set ...
    publisherAmerican Society of Civil Engineers
    titleStiffness-Embedded GNN Model for Structural Component Importance Analysis
    typeJournal Article
    journal volume40
    journal issue3
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-6920
    journal fristpage04026003-1
    journal lastpage04026003-14
    page14
    treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003
    contenttypeFulltext
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