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A Novel Satellite Traffic Flow Prediction Scheme Based on Wavelet Neural Network and Genetic Algorithm
Li Ning *,Wang Pengfei #,Han Ke,Deng Zhongliang
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100867
*Correspondence author
#Submitted by
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Funding: none
Opened online: 2 December 2015
Accepted by: none
Citation: Li Ning,Wang Pengfei,Han Ke.A Novel Satellite Traffic Flow Prediction Scheme Based on Wavelet Neural Network and Genetic Algorithm[OL]. [ 2 December 2015] http://en.paper.edu.cn/en_releasepaper/content/4664049
 
 
Satellite communications network is a kind of delay tolerant network with characters of intermittent connection, long packet queuing time, complex and uncertain delay time, etc. The call congestion rate of new business is higher in delay tolerant network which leads to the reduction of communication quality and the high error code rate. The existing traffic flow prediction scheme is hard to meet new business and individual requirements. It becomes more and more important to study the most effective traffic prediction scheme so as to increase the satellite bandwidth utilization. In this paper, BP neural network (BPNN) has been used as regression model, and the Genetic Algorithm (GA) has been used to search the weights matrix and thresholds of BP neural network. Then the satellite traffic flow prediction scheme based on wavelet neural network and genetic algorithm (WNNGA) was put forward. Simulation results with the real traffic traces show that the proposed method can more accurately predict the future of the satellite network traffic and decrease the processing time compared with previous model method.?????
Keywords:Traffic Prediction; Satellite Communications; Wavelet Neural Network; Genetic Algorithm?????
 
 
 

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