Application of Fuzzy Set Theory to Evaluate the Stability of Slopes

Abstract

An artificial intelligence tools, Adaptive Neuro Fuzzy Inference System (ANFIS), was used in this study to predict the stability of slopes. Data used in this study were 300 various designs of slope. Those designs were created by using Slope/W which calculated factors of safety using various limit equilibrium methods (LEM) such as Bishop, Spencer and Morgenstern-Price. The input parameters consisted of height of slope, H (1–10 m), unit weight of slope material, γ (15-22 kN/m3), angle of slope, θ (11.31°-78.69°), coefficient of cohesion, c (0-50 kN/m2) and internal angle of friction, (20°- 40°) and the output parameter is the factor of safety. To build the fuzzy inference system, 243 rules were used at 60 epochs. The number of membership function for the any input was three and the type of membership function for output was linear. ANFIS obtained regression square (R2) of one for Bishop, one for Janbu, one for Morgenstern-Price and one for Ordinary. The result proved that ANFIS may possibly predict the safety factor with good precision and nearly to the target data.