Cargando…
Hybrid Machine-Learning-Based Prediction Model for the Peak Dilation Angle of Rock Discontinuities
The peak dilation angle is an important mechanical feature of rock discontinuities, which is significant in assessing the mechanical behaviour of rock masses. Previous studies have shown that the efficiency and accuracy of traditional experimental methods and analytical models in determining the she...
Autores principales: | Xie, Shijie, Yao, Rubing, Yan, Yatao, Lin, Hang, Zhang, Peilei, Chen, Yifan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10573530/ https://www.ncbi.nlm.nih.gov/pubmed/37834523 http://dx.doi.org/10.3390/ma16196387 |
Ejemplares similares
-
PeakBot: machine-learning-based chromatographic peak picking
por: Bueschl, Christoph, et al.
Publicado: (2022) -
Experimental Study of Energy Evolution at a Discontinuity in Rock under Cyclic Loading and Unloading
por: Zheng, Wei, et al.
Publicado: (2022) -
Machine learning approaches to predict peak demand days of cardiovascular admissions considering environmental exposure
por: Qiu, Hang, et al.
Publicado: (2020) -
Fracture Closure Empirical Model and Theoretical Damage Model of Rock under Compression
por: Chen, Yifan, et al.
Publicado: (2023) -
The Prediction of Sinter Drums Strength Using Hybrid Machine Learning Algorithms
por: Ren, Xinying, et al.
Publicado: (2022)