Fuzzy logic based prediction of retaining wall stability

In geotechnical engineering, retaining walls are widely employed to solve the problem of supporting horizontal loads occurring between two different soil levels. In the traditional retaining wall design, stability checks continue until a safe design is obtained according to selected wall dimensions and soil properties. This design method is a process that is time-consuming and based on trial and error. In this study, the stability control of the retaining wall, which is a complex engineering design, has been carried out with fuzzy logic methods. Adaptive network-based fuzzy inference systems (ANFISs) including Grid Partition (ANFIS-GP) and Substructive Clustering (ANFIS-SC) have been utilized as fuzzy logic methods. The sliding stability criterion of the cantilever retaining wall has been obtained by performing 1024 retaining wall designs which are created using different wall dimensions. Ninety percent and ten percent of the 1024 sliding safety factor values acquired through numerical analyses were respectively allocated to the training and testing phases. The prediction performances of the methods have been evaluated by considering the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R²) obtained for the sliding safety factors during the training and testing stages. Upon juxtaposing the actual and anticipated sliding safety factors for a dataset comprising 1024 observations, it has become evident that the ANFIS-SC methodology outperforms the ANFIS-GP approach in terms of predictive accuracy. Furthermore, this analysis culminated in the determination that the application of fuzzy logic methods stands as an efficacious and dependable means for checking the stability criteria of retaining walls.