Abstract
Slope stability analysis is routinely performed due to geological instability found in earth slopes. It has been an important role in geotechnical engineering for all the times. Although the efficiency of modern technology has significantly improved, the slope stability analysis is becoming more difficult due to the existence of imprecise, uncertainties and discontinuous function in the actual scenario. Moreover, given the presence of local minima points, the position of the critical failure surface in slope stability analysis is made inaccurate and cumbersome. This work proposes a meta-heuristic based approach to locate critical failure surfaces under prevailing conditions and constraints. The reliability and efficiency of the approach are examined by investigating the benchmark case studies. The outcome results indicate that, the proposed approach could acquire acceptable performance over existing methods and attain a better solution quality in terms of accuracy and efficiency.
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Singh, J., Banka, H. (2021). A Meta-heuristic Based Approach for Slope Stability Analysis to Design an Optimal Soil Slope. In: Das, S., Das, S., Dey, N., Hassanien, AE. (eds) Machine Learning Algorithms for Industrial Applications. Studies in Computational Intelligence, vol 907. Springer, Cham. https://doi.org/10.1007/978-3-030-50641-4_12
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DOI: https://doi.org/10.1007/978-3-030-50641-4_12
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