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Deep-Learning Framework for Dynamic Deflection Prediction of Suspension Bridges under Temperature, Traffic, and Wind Loads

dc.contributor.authorWang, Zhi-wei
dc.contributor.authorZhang, Wen-ming
dc.contributor.authorLu, Xiao-fan
dc.contributor.authorFragkoulis, Vasileios C.
dc.contributor.authorBeer, Michael
dc.date.accessioned2026-08-20T21:21:15Z
dc.date.available2026-08-20T21:21:15Z
dc.date.copyright2025/11/19
dc.date.issued2026
dc.identifier.otherJBENF2.BEENG-7818.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314330
dc.description.abstractAbstract A data-driven predictive model for dynamic deflection response can aid the safe operation and maintenance of a suspension bridge. In particular, it lays the groundwork for bridge condition assessment and damage detection, dynamic reliability ...
dc.publisherAmerican Society of Civil Engineers
dc.titleDeep-Learning Framework for Dynamic Deflection Prediction of Suspension Bridges under Temperature, Traffic, and Wind Loads
dc.typeJournal Article
dc.journal.volume31
dc.journal.issue2
dc.journal.titleJournal of Bridge Engineering
dc.identifier.doi10.1061/JBENF2.BEENG-7818
dc.journal.fristpage04025100-1
dc.journal.lastpage04025100-21
dc.page21
dc.treeJournal of Bridge Engineering:;2026:;Volume ( 031 ):;issue: 002
dc.contenttypeFulltext


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