Title :
On-Line Traffic Forecasting of Mobile Communication System
Author :
Wang, Shaojun ; Guo, Jia ; Liu, Qi ; Peng, Xiyuan
Author_Institution :
Sch. of Electr. Eng. & Autom., Harbin Inst. of Technol., Harbin, China
Abstract :
To achieve the analysis of characteristic and forecasting of the mobile communication traffic, a mobile communication traffic modeling and forecasting method by Least Squares Support Vector Machine(LS-SVM) is proposed. With this method, an on-line forecasting scheme is designed to realize short-time forecasting of the mobile communication traffic. The traffic data is provided by China Mobile Communications Corporation Heilongjiang Co. Ltd. Compared with multiplicative seasonal ARIMA models, experiments and test results show that the LS-SVM solution increased the implementation efficiency greatly and improved prediction accuracy.
Keywords :
autoregressive moving average processes; least squares approximations; mobile communication; support vector machines; telecommunication computing; telecommunication traffic; ARIMA model; China mobile communication corporation; LS-SVM; least squares support vector machine; mobile communication system; online traffic forecasting; Data models; Forecasting; Mobile communication; Predictive models; Support vector machines; Time series analysis; Training; ARIMA; LS-SVM; On-line traffic Forecasting;
Conference_Titel :
Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-8043-2
Electronic_ISBN :
978-0-7695-4180-8
DOI :
10.1109/PCSPA.2010.32