(untitled) (International Journal of Engineering and Computer Science, 2017)
Artificial neural networks (ANN) usually called neural networks are very sophisticated modeling techniques which are capable of modeling extremely complex functions. They are used for predicting the outcome of two or more independent variables. Predicting the stability of slopes is a very challenging task for the geotechnical engineers. They have to pay particular attention to geology, ground water and shear strength of the soils in accessing slope stability. In this paper, a prediction formula has been developed for predicting the factor of safety (FOS) of the slopes using ANN. A total of 110 cases with different geometric and soil conditions were analyzed using Bishop’s Simplified Method. Out of these, 100 cases were used to train up the prediction model. The computational method for the training process was a back propagation learning algorithm. The prediction model is validated by comparing the results with the remaining 10 cases.