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

dc.contributor.author	Xu, Xinyu
dc.contributor.author	Zhu, Siyu
dc.contributor.author	Li, Yongle
dc.date.accessioned	2026-08-20T21:23:05Z
dc.date.available	2026-08-20T21:23:05Z
dc.date.copyright	2025/11/17
dc.date.issued	2026
dc.identifier.other	JCCEE5.CPENG-6297.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4314371
dc.description.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 ...
dc.publisher	American Society of Civil Engineers
dc.title	Adaptive Analysis for Random Response of Wind–Vehicle–Bridge System Based on a Hybrid Deep-Learning Method
dc.type	Journal Article
dc.journal.volume	40
dc.journal.issue	2
dc.journal.title	Journal of Computing in Civil Engineering
dc.identifier.doi	10.1061/JCCEE5.CPENG-6297
dc.journal.fristpage	04025133-1
dc.journal.lastpage	04025133-11
dc.page	11
dc.tree	Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 002
dc.contenttype	Fulltext