EGU26-11103, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-11103
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Prediction of Frozen Clay Strength Under Different Temperature Conditions Using Machine Learning Approaches
- Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, State Key Laboratory of Frozen Soils Engineering, China (dywang@lzb.ac.cn)
How to cite: Wang, D.: Prediction of Frozen Clay Strength Under Different Temperature Conditions Using Machine Learning Approaches, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11103, https://doi.org/10.5194/egusphere-egu26-11103, 2026.