An artificial neural network approach to inhomogeneous soil slope stability predictions based on limit analysis methods Article Swipe
Related Concepts
Stability (learning theory)
Artificial neural network
Limit analysis
Slope stability
Limit (mathematics)
Geotechnical engineering
Upper and lower bounds
Slope stability analysis
Chart
Engineering
Finite element method
Mathematics
Computer science
Structural engineering
Statistics
Mathematical analysis
Artificial intelligence
Machine learning
Zhiguang Qian
,
An-Jui Li
,
W.C. Chen
,
A. V. Lyamin
,
Jing-Cai Jiang
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1016/j.sandf.2018.10.008
· OA: W2918199868
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1016/j.sandf.2018.10.008
· OA: W2918199868
The assessment of soil slope stability is an important task in geotechnical designs. This study uses finite element upper bound (UB) and lower bound (LB) limit analysis (LA) methods to investigate inhomogeneous soil slope stability on the basis of the conventional Mohr–Coulomb parameters. The obtained stability numbers are presented in inhomogeneous soil slope stability charts. In order to minimize manual reading errors when using the chart solutions, an artificial neural network (ANN) is employed to develop a stability assessment tool for the slopes investigated in this paper. The slope stability analysis using the ANN-based tool is convenient, and the predictions it provides are highly accurate.
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