Short-Term Passenger Flow Prediction of Urban Rail Transit Integrating Multiple Features: A Hybrid Model with Two-Stage Feature Selection

dc.contributor.author	Lai, Yuanwen
dc.contributor.author	Zhang, Jiakun
dc.contributor.author	Zhou, Xiaowei
dc.contributor.author	Xu, Ling
dc.contributor.author	Lan, Ziye
dc.contributor.author	M. Easa, Said
dc.contributor.author	Wang, Shuyi
dc.date.accessioned	2026-08-20T20:57:16Z
dc.date.available	2026-08-20T20:57:16Z
dc.date.copyright	2026/03/27
dc.date.issued	2026
dc.identifier.other	JTEPBS.TEENG-9429.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4313725
dc.description.abstract	AbstractUrban rail transit systems encounter challenges in short-term passenger flow prediction due to complex spatiotemporal data and dynamic travel patterns. Traditional models often struggle to capture these complexities. This study introduces a hybrid ...
dc.publisher	American Society of Civil Engineers
dc.title	Short-Term Passenger Flow Prediction of Urban Rail Transit Integrating Multiple Features: A Hybrid Model with Two-Stage Feature Selection
dc.type	Journal Article
dc.journal.volume	152
dc.journal.issue	6
dc.journal.title	Journal of Transportation Engineering, Part A: Systems
dc.identifier.doi	10.1061/JTEPBS.TEENG-9429
dc.journal.fristpage	04026027-1
dc.journal.lastpage	04026027-17
dc.page	17
dc.tree	Journal of Transportation Engineering, Part A: Systems:;2026:;Volume ( 152 ):;issue: 006
dc.contenttype	Fulltext