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

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

1

Lastpage

4

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4994-1

Type

conf

DOI

10.1109/ICIECS.2009.5363679

Filename

5363679