%0 Journal Article
%A WU Wentie
%A SONG Yuecong
%A LI Min
%T Chaotic prediction of network traffic based on neural network optimized by ant colony optimization algorithm
%D 2012
%R
%J Computer Engineering and Applications
%P 97-101
%V 48
%N 34
%X In order to improve the prediction accuracy of network traffic, this paper proposes a network traffic prediction model based on neural network optimized by ant colony optimization algorithm（ACO-BPNN）. The data of network traffic are reconstructed by chaotic theory. The parameters of BPNN are considered the position vector of ants. The optimal parameters are found by ant colony optimization algorithm. The optimal model for network traffic is built and the performance of mode are tested by network traffic data. The simulation results show that ACO-PBNN can describe the change rule of network traffic accurately and can improve prediction accuracy.
%U http://cea.ceaj.org/EN/abstract/article_29705.shtml