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

被引:3
作者
Vu, Vu Truong [1 ]
机构
[1] Nguyen Tat Thanh Univ, Fac Civil Engn, 300A Nguyen Tat Thanh,Ward 13,Dist 4, Ho Chi Minh City, Vietnam
关键词
Slope stability; Differential evolution; Artificial neural network; Optimization; Limit equilibrium method; FAILURE SURFACE;
D O I
10.2478/cee-2023-0026
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页码:288 / 300
页数:13
相关论文
共 13 条
[1]  
Bishop A.W., 1955, Geotechnique, V5, P7, DOI 10.1680/geot.1955.5.1.7
[2]  
Fellenius W., 1936, T 2 C LARGE DAMS, V4, P445
[3]   Search for critical slip circle using genetic algorithms [J].
Goh, ATC .
CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS, 2000, 17 (03) :181-211
[4]   Determination of the critical failure surface for slope stability analysis using ant colony optimization [J].
Kahatadeniya, K. S. ;
Nanakorn, P. ;
Neaupane, K. M. .
ENGINEERING GEOLOGY, 2009, 108 (1-2) :133-141
[5]   Locating the general failure surface of earth slope using particle swarm optimisation [J].
Khajehzadeh, Mohammad ;
Taha, Mohd Raihan ;
El-Shafie, Ahmed ;
Eslami, Mahdiyeh .
CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS, 2012, 29 (01) :41-57
[6]   An artificial neural network approach to inhomogeneous soil slope stability predictions based on limit analysis methods [J].
Qian, Z. G. ;
Li, A. J. ;
Chen, W. C. ;
Lyamin, A., V ;
Jiang, J. C. .
SOILS AND FOUNDATIONS, 2019, 59 (02) :556-569
[7]  
Rumelhart DE, 1986, Parallel Distributed Processing: Explorations in the Microstructure of Cognition, V1, P318
[8]   A study of slope stability prediction using neural networks [J].
Sakellariou, M. ;
Ferentinou, M. .
GEOTECHNICAL AND GEOLOGICAL ENGINEERING, 2005, 23 (04) :419-445
[9]   Utilization of a least square support vector machine (LSSVM) for slope stability analysis [J].
Samui, P. ;
Kothari, D. P. .
SCIENTIA IRANICA, 2011, 18 (01) :53-58
[10]   Slope stability analysis: a support vector machine approach [J].
Samui, Pijush .
ENVIRONMENTAL GEOLOGY, 2008, 56 (02) :255-267