| contributor author | Sun, Kai | |
| contributor author | Li, Zhiqing | |
| contributor author | Wang, Haosen | |
| contributor author | Kong, Youxing | |
| contributor author | Wang, Shuangjiao | |
| contributor author | Zhou, Yingxin | |
| contributor author | Hu, Ruilin | |
| date accessioned | 2026-08-20T11:08:58Z | |
| date available | 2026-08-20T11:08:58Z | |
| date copyright | 2025/08/13 | |
| date issued | 2025 | |
| identifier other | IJGNAI.GMENG-10984.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4311759 | |
| description abstract | Abstract Machine learning is extensively used in constitutive modeling of geomaterials and
is critical for enhancing computational analyses in geotechnical engineering. In the
area of geomechanical modeling, the primary application of machine learning ... | |
| publisher | American Society of Civil Engineers | |
| title | Integrated Machine Learning Using Autoencoder and Multilayer Perceptron Approaches to Predict Stress–Strain Curves of Frozen Soil–Rock Mixtures | |
| type | Journal Article | |
| journal volume | 25 | |
| journal issue | 10 | |
| journal title | International Journal of Geomechanics | |
| identifier doi | 10.1061/IJGNAI.GMENG-10984 | |
| journal fristpage | 04025229-1 | |
| journal lastpage | 04025229-15 | |
| page | 15 | |
| tree | International Journal of Geomechanics:;2025:;Volume ( 025 ):;issue: 010 | |
| contenttype | Fulltext | |
