ESTIMATION OF SOIL LIQUEFACTION POTENTIAL IN THE DALAMAN RESIDENTIAL AREA USING A SUPERVISED MACHINE LEARNING MODEL

Liquefaction is a critical phenomenon in geotechnical engineering, especially in mixed depositional environments where different soil types coexist. In such environments, assessment of liquefaction potential may be challenging. However, machine learning techniques overcome these challenges. In this study, to estimate the liquefaction potentials of the soils in the Dalaman residential area which is situated in a mixed depositional environment, supervised Multilayer Perceptron (MLP) model has been generated by using seismic parameters from the Chi-Chi and Kocaeli earthquakes and the parameters of the soils affected by these earthquakes. Sensitivity, specificity, accuracy, precision F1 score and AUC have been calculated for training and testing phases in model generation stage and for Dalaman Region. These values have been found to be 77.9%, 91.5, 85.7%, 87.0%, 0.822 and 0.930 in training phase; 80%, 83.1%, 81.8%, 75%, 0.774 and 0.930 in testing phase. For Dalaman residential area, these values have been found as 81.3%, 86.2%, 83.5%, 87.25% and 0.841. When the values from training and testing phase are compared to the results of Dalaman Region, it can be said that the model accurately estimated the liquefaction potentials of the soils in the Dalaman residential area.