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Stiffness-Embedded GNN Model for Structural Component Importance Analysis

dc.contributor.authorJi, Xiaolong
dc.contributor.authorWei, Kedong
dc.contributor.authorChen, Zhaohui
dc.contributor.authorLiu, Yu
dc.date.accessioned2026-08-20T21:26:26Z
dc.date.available2026-08-20T21:26:26Z
dc.date.copyright2026/01/21
dc.date.issued2026
dc.identifier.otherJCCEE5.CPENG-6920.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314455
dc.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 ...
dc.publisherAmerican Society of Civil Engineers
dc.titleStiffness-Embedded GNN Model for Structural Component Importance Analysis
dc.typeJournal Article
dc.journal.volume40
dc.journal.issue3
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-6920
dc.journal.fristpage04026003-1
dc.journal.lastpage04026003-14
dc.page14
dc.treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003
dc.contenttypeFulltext


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