Application of support vector machines in ground subsidence forecasting

Based on the statistical learning theory(SLT) and the empirical risk minimization(ERM) principle,the support vector machines(SVM) theory was applied to the prediction of ground subsidence.Compared to BP neural network method,the SVM was proved to be faster in computation and had better generalization performance.