Slope Reliability Analysis Using a Convolutional Neural Networks Surrogate Model with Emphasis on the Nonstationary Spatial Variability of Soil Properties

dc.contributor.author	Zhang, Sheng
dc.contributor.author	Ding, Li
dc.contributor.author	Yang, Rui
dc.contributor.author	Zhang, Feng
dc.contributor.author	Tong, Chen-Xi
dc.date.accessioned	2026-08-20T11:59:14Z
dc.date.available	2026-08-20T11:59:14Z
dc.date.copyright	2025/11/26
dc.date.issued	2026
dc.identifier.other	IJGNAI.GMENG-11760.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4312937
dc.description.abstract	Abstract Slope reliability analysis has always been a research focus for geotechnical engineers. Currently, most studies use stationary random fields to simulate the spatial variability of soil parameters. However, many field test data show that soil ...
dc.publisher	American Society of Civil Engineers
dc.title	Slope Reliability Analysis Using a Convolutional Neural Networks Surrogate Model with Emphasis on the Nonstationary Spatial Variability of Soil Properties
dc.type	Journal Article
dc.journal.volume	26
dc.journal.issue	2
dc.journal.title	International Journal of Geomechanics
dc.identifier.doi	10.1061/IJGNAI.GMENG-11760
dc.journal.fristpage	04025338-1
dc.journal.lastpage	04025338-14
dc.page	14
dc.tree	International Journal of Geomechanics:;2026:;Volume ( 026 ):;issue: 002
dc.contenttype	Fulltext