Prediction of pile bearing capacity using support vector machine

This paper examines the potential of support vector machine (SVM) in prediction of bearing capacity of pile from pile load test data. In this study, SVM uses regression technique by introducing e-insensitive loss function. The data from a pile load test has been used to build the SVM model. SVM uses penetration depth ratio (l/d), mean normal stress (sigma(m)), and no of blows (n) as input parameters. The output of SVM model is bearing capacity (Q) of pile. Sensitivity analysis of the develop SVM model shows that l/d has the most significant effect on Q. An equation has been also developed for the prediction of bearing capacity of pile. This study shows that SVM approach give an alternative tools to geotechnical engineers for the determination of bearing capacity of pile.