SVM in Predicting the Deformation of Deep Foundation Pit in Soft Soil Area

Abstract

Based on the measured deformation data series, future deformation value of deep foundation pit was predicted using Support Vector Machine (SVM) model in soft soil area. Gauss kernel function, Sequential minimal optimization arithmetic, and the parameter value of C andε were determined by testing. By using the method in example, results are shown to be in good agreement with measured data and laws reported in paper, and illustrates that SVM could perform well in solving fuzzy geotechnical engineering problem similar to deformation prediction. As another act, the method and conclusion can be considered as reference for colleagues.