Influence of Sampling Methods on the Accuracy of Machine Learning Predictions Used for Strain-Dependent Slope Stability
Abstract
:1. Introduction
2. Enhanced Strain-Dependent Slope Stability Using Machine Learning
2.1. Strain-Dependent Slope Stability (SDSS)
2.2. Implementation of SDSS
2.3. Application of Machine Learning in SDSS
3. Sampling
3.1. Motivation
3.2. Modified Sampling Approaches
3.3. Influence of Sampling Approach on Accuracy of MLP Prediction
4. Influence of Sampling on the FoS for Slopes Subjected to Different Loading
4.1. Methodology
4.2. Results and Discussion
5. Conclusions and Future Work
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
ANN | Artificial neural network |
DSS | Direct simple shear |
FoS | Factor of safety |
ID | Incremental Driver |
IGS | Intergranular strain |
KNN | K-nearest neighbors |
LHS | Latin hypercube sampling |
ML | Machine learning |
MLP | Multilayer perceptron |
RBF | Radial basis functions |
RF | Random forest |
SDSS | Strain-dependent slope stability |
SVM | Suppor vector machines |
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Overall | ||||
---|---|---|---|---|
Grid sampling with linear spacing | 0.000 | 0.313 | 0.858 | 0.773 |
Grid sampling with quadratic spacing | 0.000 | 0.750 | 0.934 | 0.887 |
Monte Carlo sampling | 0.011 | 0.642 | 0.938 | 0.879 |
Latin hypercube sampling | 0.003 | 0.603 | 0.878 | 0.823 |
Modified Latin hypercube sampling-1 | 0.328 | 0.856 | 0.936 | 0.913 |
Modified Latin hypercube sampling-2 | 0.769 | 0.823 | 0.917 | 0.907 |
in ° | hs in MPa | n | |||||
---|---|---|---|---|---|---|---|
33.1 | 4000 | 0.27 | 0.677 | 1.054 | 1.212 | 0.14 | 2.5 |
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Shakya, S.; Schmüdderich, C.; Machaček, J.; Prada-Sarmiento, L.F.; Wichtmann, T. Influence of Sampling Methods on the Accuracy of Machine Learning Predictions Used for Strain-Dependent Slope Stability. Geosciences 2024, 14, 44. https://doi.org/10.3390/geosciences14020044
Shakya S, Schmüdderich C, Machaček J, Prada-Sarmiento LF, Wichtmann T. Influence of Sampling Methods on the Accuracy of Machine Learning Predictions Used for Strain-Dependent Slope Stability. Geosciences. 2024; 14(2):44. https://doi.org/10.3390/geosciences14020044
Chicago/Turabian StyleShakya, Sudan, Christoph Schmüdderich, Jan Machaček, Luis Felipe Prada-Sarmiento, and Torsten Wichtmann. 2024. "Influence of Sampling Methods on the Accuracy of Machine Learning Predictions Used for Strain-Dependent Slope Stability" Geosciences 14, no. 2: 44. https://doi.org/10.3390/geosciences14020044