Forecasting method of temporal data based on support vector regress machine
Zhiqing Meng · Computer Engineering and Applications Journal · 2007
Support Vector Regress machine(SVR) will be a promising method in temporal data forecasting fields because it uses a risk function consisting of the empirical error and a regularized term which is derived from the structural risk minimization principle.This paper briefly introduces the basic theory of Support Vector Regress(SVR) and applies SVR to create a model,which also can be used for forecasting the multi-attribute temporal data and the temporal data.The result of simulation shows that SVR is superior to BP Neutral Network in the stability and accuracy.