%0 Journal Article
%A ZHANG Xin
%A WANG Bing
%A ZHAO Pu
%T SSVR algorithm and time series prediction of furnace combustion state
%D 2008
%R
%J Computer Engineering and Applications
%P 205-207
%V 44
%N 14
%X The Support Vector Regression(SVR) is used for the time series analysis and prediction to resolve the complex nonlinear system modeling problems.The smooth method is introduced to improve the standard SVR algorithm in order to reduce calculation complexity.In this paper,the Smooth Support Vector Regression(SSVR)is applied for the time series prediction of furnace combustion states.By clustering and analyzing the furnace flame images,calculated the state coefficient denoting the furnace combustion states,constructed the state coefficient time series,and built the prediction model using the SSVR algorithm.The experimental results show that SSVR has faster convergence speed and higher fitting and prediction precision,which effectively extends the application of SVR.
%U http://cea.ceaj.org/EN/abstract/article_17037.shtml