Slope Deformation Prediction Based on Support Vector Machine

Abstract

This paper principally studies the prediction of slope deformation based on Support Vector Machine (SVM). In the prediction process，explore how to reconstruct the phase space. The geological body’s displacement data obtained from chaotic time series are used as SVM’s training samples. Slope displacement caused by multivariable coupling is predicted by means of single variable. Results show that this model is of high fitting accuracy and generalization, and provides reference for deformation prediction in slope engineering.

Keywords

• Deformation Prediction
• Chaotic Time Series
• Phase-space Reconstruction
• Average Mutual Information Method