Title :
LS-SVM Based Prediction of the Size of Internet User in China
Author :
Deng, Changshou ; Zhao, Bingyan
Author_Institution :
Sch. of Inf. Sci. & Technol., Jiujiang Univ., Jiujiang, China
Abstract :
It is very useful to predict the growth of internet user in China. A least square support vector machine regression model was introduced. Firstly, phase space reconstruction technology was used to deal with time series data, then with LSSVM, a method to predict the number of Internet user was constructed. The numerical experiments show that the accuracy of this prediction model has great advantage compared with the Grey theory and linear regression-based prediction model. It is a good alternative to predict the growth of Internet in China.
Keywords :
Internet; least squares approximations; regression analysis; support vector machines; Grey theory; Internet user; LS-SVM based prediction; least square support vector machine regression model; linear regression-based prediction model; time series data; Cities and towns; Equations; Government; Internet; Least squares methods; Predictive models; Risk management; Space technology; Support vector machine classification; Support vector machines;
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
DOI :
10.1109/ICIECS.2009.5363679