Uncertainty Quantification in Stochastic Subspace Identification Using a Simulation Method with DBSCAN-Based Outlier Detection

dc.contributor.author	Wang, Yi
dc.contributor.author	Wang, Jia
dc.contributor.author	Hua, Xugang
dc.contributor.author	Niu, Huawei
dc.contributor.author	Feng, Zhouquan
dc.date.accessioned	2026-08-20T21:13:52Z
dc.date.available	2026-08-20T21:13:52Z
dc.date.copyright	2025/10/22
dc.date.issued	2026
dc.identifier.other	AJRUA6.RUENG-1658.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4314153
dc.description.abstract	AbstractThere are variance errors in the modal parameters estimated by stochastic subspace identification (SSI), with specified model order and time lag parameter. To quantify the variance of the identified modal parameters, the commonly used computation ...
dc.publisher	American Society of Civil Engineers
dc.title	Uncertainty Quantification in Stochastic Subspace Identification Using a Simulation Method with DBSCAN-Based Outlier Detection
dc.type	Journal Article
dc.journal.volume	12
dc.journal.issue	1
dc.journal.title	ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
dc.identifier.doi	10.1061/AJRUA6.RUENG-1658
dc.journal.fristpage	04025087-1
dc.journal.lastpage	04025087-17
dc.page	17
dc.tree	ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2026:;Volume ( 012 ):;issue: 001
dc.contenttype	Fulltext