Stability Assessment Model for Epimetamorphic Rock Slopes based on Adaptive Neuro-Fuzzy Inference System

Neuro-fuzzy inference systems have been used in many areas in civil engineering applications. A stability assessment model for epimetamorphic rock slopes has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS) for its capacity of dynamic nonlinear analyses. In the present study the inference system is employed to predict the stability of the slope by choosing bulk density γ, the height H, the inclination β, the shear strength parameters c and φ, of the slope as inputs, while the stability state as output. 53 slope cases in the author’s research projects, i.e. 53 input-output data pairs were extracted, of which 41 pairs (training data set) were used for training the ANFIS while the remaining 12 pairs (checking data set) were used for validating the identified model. It is observed that the checking results of ANFIS model coincide with the actual stability state of epimetamorphic rock slopes, which outperforms the BP neural network model by contrast. Lastly, the ANFIS model was employed to predict the stability of Wangjiazhai slope, the fine prediction capability for the stability of epimetamorphic rock slopes was verified again.