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Telecommunication traffic forecasting based on BP neural network trained by PSO
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Telecommunication traffic forecasting based on BP neural network which is optimized by particle swarm optimization (PSO) algorithm is presented. PSO is a novel random optimization method based on swarm intelligence, which has more powerful ability of global optimization. Here, we use the telecommunication traffic ranging fi'om 1989 to 2005 in China as the sample to the neural network, which has been trained by PSO, are employed to illustrate the presented model. The experimental results prove that the proposed method optimized by PSO can quicken the learning speed of the network and improve the forecasting precision compared with the conventional BP method and show that the method is not only simple to calculate, but also practical and effective.
DONG Xian、XU Bing-ji
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School of information Engineering, China University of Geosciences, Beijng 100083, China
BP neural network particle swarm optimization telecommunication traffic forecasting
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