Dual-Modal Feature Learning Approach for Probabilistic Semisupervised Interpretation of Subsurface Stratigraphy from Sparse Boreholes and Cone Penetration Tests

dc.contributor.author	Qian, Zehang
dc.contributor.author	Shi, Chao
dc.contributor.author	Lee, Siew-Wei
dc.date.accessioned	2026-08-20T10:58:39Z
dc.date.available	2026-08-20T10:58:39Z
dc.date.copyright	2026/01/05
dc.date.issued	2026
dc.identifier.other	JGGEFK.GTENG-14409.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4311523
dc.description.abstract	AbstractProbabilistic interpretation of subsurface stratigraphy from sparse boreholes and cone penetration tests (CPTs) remains a critical yet nontrivial task in geotechnical site characterization. The challenge primarily arises from three key factors: (1)...
dc.publisher	American Society of Civil Engineers
dc.title	Dual-Modal Feature Learning Approach for Probabilistic Semisupervised Interpretation of Subsurface Stratigraphy from Sparse Boreholes and Cone Penetration Tests
dc.type	Journal Article
dc.journal.volume	152
dc.journal.issue	3
dc.journal.title	Journal of Geotechnical and Geoenvironmental Engineering
dc.identifier.doi	10.1061/JGGEFK.GTENG-14409
dc.journal.fristpage	04026001-1
dc.journal.lastpage	04026001-19
dc.page	19
dc.tree	Journal of Geotechnical and Geoenvironmental Engineering:;2026:;Volume ( 152 ):;issue: 003
dc.contenttype	Fulltext