Combination forecasting based on Support Vector Machine and its application

In this paper, we first introduce the principles and methods of Support Vector Machine (SVM), then give the methods of determining weights of combination forecasting using Support Vector Machine. This method can overcome the shortcoming of the other combination forecasting, which keeps smaller fitting error and higher forecasting accuracy, therefore the effect of forecasting is greatly promoted. At last, this method is applied to forecast the total number of health personnels of Hebei province. Contrast trial indicates that this method possesses fast operation velocity and good generalization performance.