Artificial intelligence application for predicting slope stability on soft ground: a comparative study

This paper aimed to estimate the slope stability on soft ground by utilising Artificial Intelligence (AI) method that is widely used in the past decade for prediction purposes. The slope stability is predicted using Factor of Safety (FoS) that is generated with Limit Equilibrium Method (LEM) such as Ordinary, Bishop, Janbu and Morgenstern–Price and the total of 233 random datasets in this study. The output of the FoS is also estimated using the input parameters of height of slope (H), unit weight slope aterial (γ), angle of slope (θ), Coefficient of cohesion (c), and internal angle friction (ϕ) that are proceeded with Artificial Neural Networks (ANN) and Adaptive Neural Fuzzy-Logic Inference Systems (ANFIS). The final selected model of the slope stability is tested with the real data to produce a better result of the potential prediction in the accepted range of accuracy.