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Identifying Critical Category Combinations of Bridge Cables at Risk of Internal Resonances Using Data Mining Technology

dc.contributor.authorChen, Kefan
dc.contributor.authorHou, Wei
dc.contributor.authorLi, Zhenkun
dc.contributor.authorRen, Xiangwei
dc.contributor.authorLin, Weiwei
dc.date.accessioned2026-08-20T21:20:20Z
dc.date.available2026-08-20T21:20:20Z
dc.date.copyright2025/10/17
dc.date.issued2026
dc.identifier.otherJBENF2.BEENG-7616.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314310
dc.description.abstractAbstract Fan-shaped cable nets in cable-stayed bridges (CSBs) exhibit a dense spectrum of local frequencies, some of which inevitably lie close to global frequencies. This proximity increases the risk of internal resonances (IRs) in the system, posing an ...
dc.publisherAmerican Society of Civil Engineers
dc.titleIdentifying Critical Category Combinations of Bridge Cables at Risk of Internal Resonances Using Data Mining Technology
dc.typeJournal Article
dc.journal.volume31
dc.journal.issue1
dc.journal.titleJournal of Bridge Engineering
dc.identifier.doi10.1061/JBENF2.BEENG-7616
dc.journal.fristpage04025085-1
dc.journal.lastpage04025085-13
dc.page13
dc.treeJournal of Bridge Engineering:;2026:;Volume ( 031 ):;issue: 001
dc.contenttypeFulltext


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