Model of Least Square Support Vector Machine (LSSVM) for Prediction of Fracture Parameters of Concrete

Abstract

This article employs Least Square Support Vector Machine (LSSVM) for determination of fracture parameters of concrete: critical stress intensity factor (K s Ic ) and the critical crack tip opening displacement (CTODc). LSSVM that is firmly based on the theory of statistical learning theory uses regression technique. The results are compared with a widely used Artificial Neural Network (ANN) Models of LSSVM have been developed for prediction of K s Ic and CTODc, and then a sensitivity analysis has been performed to investigate the importance of the input parameters. Equations have been also developed for determination of K s Ic and CTODc. The developed LSSVM also gives error bar. The results show that the developed model of LSSVM is very predictable in order to determine fracture parameters of concrete.