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http://dx.doi.org/10.7843/kgs.2022.38.8.39

Prediction of Slope Failure Arc Using Multilayer Perceptron  

Ma, Jeehoon (Dept. of Civil and Environmental Eng., Yonsei Univ.)
Yun, Tae Sup (Dept. of Civil and Environmental Eng., Yonsei Univ.)
Publication Information
Journal of the Korean Geotechnical Society / v.38, no.8, 2022 , pp. 39-52 More about this Journal
Abstract
Multilayer perceptron neural network was trained to determine the factor of safety and slip surface of the slope. Slope geometry is a simple slope based on Korean design standards, and the case of dry and existing groundwater levels are both considered, and the properties of the soil composing the slope are considered to be sandy soil including fine particles. When curating the data required for model training, slope stability analysis was performed in 42,000 cases using the limit equilibrium method. Steady-state seepage analysis of groundwater was also performed, and the results generated were applied to slope stability analysis. Results show that the multilayer perceptron model can predict the factor of safety and failure arc with high performance when the slope's physical properties data are input. A method for quantitative validation of the model performance is presented.
Keywords
Matric suction; Multi-layer perceptron; Seepage analysis; Slip surface validation; Slope stability analysis;
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Times Cited By KSCI : 2  (Citation Analysis)
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