<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study aims for two purposes: firstly, using the Differential Evolution method combined with limit equilibrium methods to find the factor of safety of a variety of different configurations of slopes and soil parameters. Two patterns of the embankments are assessed, a one-layer soil pattern with 540 cases and a two-layer soil pattern with 24300 cases. Secondly, using these data to train and test an artificial neural network for predicting the factor of safety of slopes. The experimental data and values predicted by the artificial neural network correlate well with a linear coefficient of correlation of around 0.99. Given large enough training data, the proposed approach shows its reliability in quick evaluation of the slope stability without a long process of searching for a critical slip surface.</p>
</abstract>

This study aims for two purposes: firstly, using the Differential Evolution method combined with limit equilibrium methods to find the factor of safety of a variety of different configurations of slopes and soil parameters. Two patterns of the embankments are assessed, a one-layer soil pattern with 540 cases and a two-layer soil pattern with 24300 cases. Secondly, using these data to train and test an artificial neural network for predicting the factor of safety of slopes. The experimental data and values predicted by the artificial neural network correlate well with a linear coefficient of correlation of around 0.99. Given large enough training data, the proposed approach shows its reliability in quick evaluation of the slope stability without a long process of searching for a critical slip surface.

Assessment of Slope Stability with the Assistance of Artificial Neural Network and Differential Evolution

Civil and Environmental Engineering

This work is licensed under the Creative Commons Attribution 4.0 International License.

This study aims for two purposes: firstly, using the Differential Evolution method combined with limit equilibrium methods to find the factor of safety of a...

Assessment of Slope Stability with the Assistance of Artificial Neural Network and Differential Evolution

Online veröffentlicht: 12. Mai 2023

Seitenbereich: 288 - 300

DOI: https://doi.org/10.2478/cee-2023-0026

Schlüsselwörter
Slope stability, Differential evolution, Artificial neural network, Optimization, Limit equilibrium method

© 2023 Vu Truong Vu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Assessment of Slope Stability with the Assistance of Artificial Neural Network and Differential Evolution

Online veröffentlicht: 12. Mai 2023

Seitenbereich: 288 - 300

DOI: https://doi.org/10.2478/cee-2023-0026

SchlüsselwörterSlope stability, Differential evolution, Artificial neural network, Optimization, Limit equilibrium method

© 2023 Vu Truong Vu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Slope stability, Differential evolution, Artificial neural network, Optimization, Limit equilibrium method