Comprehensive review of machine learning in geotechnical reliability analysis: Algorithms, applications and further challenges
W Zhang, X Gu, L Hong, L Han, L Wang - Applied Soft Computing, 2023 - Elsevier
Geotechnical reliability analysis provides a novel way to rationally take the underlying
geotechnical uncertainties into account and evaluate the stability of geotechnical structures …
geotechnical uncertainties into account and evaluate the stability of geotechnical structures …
[HTML][HTML] Probabilistic assessment of slope failure considering anisotropic spatial variability of soil properties
L Chen, W Zhang, F Chen, D Gu, L Wang, Z Wang - Geoscience Frontiers, 2022 - Elsevier
Anisotropic spatial variability of soil properties is frequently encountered in geotechnical
engineering practice due to the complex depositional process. To quantitatively evaluate the …
engineering practice due to the complex depositional process. To quantitatively evaluate the …
Machine learning models for predicting the residual value of heavy construction equipment: An evaluation of modified decision tree, LightGBM, and XGBoost …
It is challenging to develop accurate models for heavy construction equipment residual
value prediction using conventional approaches. This article proposes three Machine …
value prediction using conventional approaches. This article proposes three Machine …
[HTML][HTML] Slope stability prediction using ensemble learning techniques: A case study in Yunyang County, Chongqing, China
W Zhang, H Li, L Han, L Chen, L Wang - Journal of Rock Mechanics and …, 2022 - Elsevier
Slope stability prediction plays a significant role in landslide disaster prevention and
mitigation. This study develops an ensemble learning-based method to predict the slope …
mitigation. This study develops an ensemble learning-based method to predict the slope …
Quantification of model uncertainty and variability for landslide displacement prediction based on Monte Carlo simulation
L Wang, T Xiao, S Liu, W Zhang, B Yang, L Chen - Gondwana Research, 2023 - Elsevier
Reliable and accurate prediction of landslide displacement is essential for early warning
systems, as well as for disaster prevention and mitigation. Machine learning and deep …
systems, as well as for disaster prevention and mitigation. Machine learning and deep …
Optimization of random forest through the use of MVO, GWO and MFO in evaluating the stability of underground entry-type excavations
The stability evaluation of underground entry-type excavations is a prerequisite of the entry-
type mining method, which directly affects whether workers can be provided with a safe and …
type mining method, which directly affects whether workers can be provided with a safe and …
Efficient time-variant reliability analysis of Bazimen landslide in the Three Gorges Reservoir Area using XGBoost and LightGBM algorithms
W Zhang, C Wu, L Tang, X Gu, L Wang - Gondwana Research, 2023 - Elsevier
Abstract The Three Gorges Reservoir Area (TGRA) is one of the most important areas for
landslide prevention and mitigation in China. Rational reliability analysis of reservoir slope …
landslide prevention and mitigation in China. Rational reliability analysis of reservoir slope …
Deep learning methods for time-dependent reliability analysis of reservoir slopes in spatially variable soils
Abstract The Three Gorges Reservoir Area (TGRA) is one of the most important landslide-
prone regions in China, and rational stability evaluation of reservoir slopes in it is of great …
prone regions in China, and rational stability evaluation of reservoir slopes in it is of great …
Displacement prediction of Jiuxianping landslide using gated recurrent unit (GRU) networks
W Zhang, H Li, L Tang, X Gu, L Wang, L Wang - Acta Geotechnica, 2022 - Springer
Displacement prediction plays a significant role in the landslide disaster early warning.
However, landslide deformation is a complex nonlinear dynamic process, posing difficulties …
However, landslide deformation is a complex nonlinear dynamic process, posing difficulties …
[HTML][HTML] Predicting student's dropout in university classes using two-layer ensemble machine learning approach: A novel stacked generalization
Student dropout is a serious problem globally. It affects not only the individual who drops out
but also the former school, family, and society in general. With the current development of …
but also the former school, family, and society in general. With the current development of …