Abstract
Slope stability analysis is one of the most important problems in geotechnical engineering. The development in slope stability analysis has followed the development in computational geotechnical engineering. This paper discusses the application of different recently developed artificial neural network models to slope stability analysis based on the actual slope failure database available in the literature. Different ANN models are developed to classify the slope as stable or unstable (failed) and to predict the factor of safety. The developed ANN model is found to be efficient compared with other methods like support vector machine and genetic programming available in literature. Prediction models are presented based on the developed ANN model parameters. Different sensitivity analyses are made to identify the important input parameters.
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Das, S.K., Biswal, R.K., Sivakugan, N. et al. Classification of slopes and prediction of factor of safety using differential evolution neural networks. Environ Earth Sci 64, 201–210 (2011). https://doi.org/10.1007/s12665-010-0839-1
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DOI: https://doi.org/10.1007/s12665-010-0839-1