Dam deformation forecasting model based on least squares support vector machine
Ming Xuan He, Xue Gui-yu · Northwest Hydropower · 2011
Deformation is the most direct and reliable reflection of structural state and safety situation in a dam,which is one of the key items in dam safety monitoring.Dam deformation is strongly non-linear and sometimes the effect of traditional forecasting methods is not very precise.Support vector machine based on statistical learning theory and structural risk minimization principle can deal with small samples,non-linear,high-dimensional problems more effectively.This paper introduces the LS-SVM which is an extension of support vector machines,and a dam deformation prediction model based on the LS-SVM was established according to the ideas of stepwise regression statistical model.Through calculation of Jinshuitan dam deformation,the results show this method is feasible and superior.