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- Title
Local Minimax Probability Machine Forecasting of Wireless Network Traffic.
- Authors
Yuan HUANG; Yanqi CHEN; Xingwei LIU
- Abstract
With the growing application of wireless networks, there are increasing security issues. The forecasting technologies for network traffic are effectively used to deal with these emerging problems. However, because the wireless network traffic has several characteristics such as nonlinearity and bursty, the classical methods could be scarcely applied to the increasingly complicated wireless network traffic problems. Minimax Probability Machine (MPM) is a recently intelligent algorithm used to deal with model for wireless network traffic. Like global SVM, global MPM has the same shortcomings on the forecast accuracy and computational complexity. Therefore, a local MPM algorithm, LMPM, is proposed in this paper, and experimental results show that forecasting accuracy and real-time computing capability of LMPM are much better than that ofglobal MPM.
- Subjects
MANAGEMENT of wireless communication systems; WIRELESS communications performance; CHEBYSHEV approximation; COMPUTATIONAL complexity; ACCESS control; APPROXIMATION algorithms
- Publication
Journal of Computer Science & Control Systems, 2013, Vol 6, Issue 2, p13
- ISSN
1844-6043
- Publication type
Article