| dc.contributor.author | Jang, Hansol | |
| dc.contributor.author | Han, Sangyoung | |
| dc.contributor.author | Bayrak, Oguzhan | |
| dc.date.accessioned | 2026-08-20T12:18:33Z | |
| dc.date.available | 2026-08-20T12:18:33Z | |
| dc.date.copyright | 2025/06/09 | |
| dc.date.issued | 2025 | |
| dc.identifier.other | JSENDH.STENG-14496.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4313344 | |
| dc.description.abstract | AbstractThis study presents a novel approach that integrates shear failure modes as critical
variables within machine learning models to enhance the accuracy of shear strength
estimation for pretensioned concrete girders. Estimating the shear strength of ... | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | Data-Driven Machine Learning for Predicting the Strength of Pretensioned Concrete Girders Considering Shear Failure Mode | |
| dc.type | Journal Article | |
| dc.journal.volume | 151 | |
| dc.journal.issue | 8 | |
| dc.journal.title | Journal of Structural Engineering | |
| dc.identifier.doi | 10.1061/JSENDH.STENG-14496 | |
| dc.journal.fristpage | 04025116-1 | |
| dc.journal.lastpage | 04025116-12 | |
| dc.page | 12 | |
| dc.tree | Journal of Structural Engineering:;2025:;Volume ( 151 ):;issue: 008 | |
| dc.contenttype | Fulltext | |
