@inproceedings{f36350a9d0024726b132b2af54058a5a,
title = "On-line traffic forecasting of mobile communication system",
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 = "ARIMA, LS-SVM, On-line traffic forecasting",
author = "Shaojun Wang and Jia Guo and Qi Liu and Xiyuan Peng",
year = "2010",
doi = "10.1109/PCSPA.2010.32",
language = "英语",
isbn = "9780769541808",
series = "Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010",
pages = "97--100",
booktitle = "Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010",
note = "1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 ; Conference date: 17-09-2010 Through 19-09-2010",
}