| contributor author | Jang, Hansol | |
| contributor author | Han, Sangyoung | |
| contributor author | Bayrak, Oguzhan | |
| date accessioned | 2026-08-20T12:18:33Z | |
| date available | 2026-08-20T12:18:33Z | |
| date copyright | 2025/06/09 | |
| date issued | 2025 | |
| identifier other | JSENDH.STENG-14496.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4313344 | |
| 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 ... | |
| publisher | American Society of Civil Engineers | |
| title | Data-Driven Machine Learning for Predicting the Strength of Pretensioned Concrete Girders Considering Shear Failure Mode | |
| type | Journal Article | |
| journal volume | 151 | |
| journal issue | 8 | |
| journal title | Journal of Structural Engineering | |
| identifier doi | 10.1061/JSENDH.STENG-14496 | |
| journal fristpage | 04025116-1 | |
| journal lastpage | 04025116-12 | |
| page | 12 | |
| tree | Journal of Structural Engineering:;2025:;Volume ( 151 ):;issue: 008 | |
| contenttype | Fulltext | |