关键词: 网络流量, 蚁群优化算法, 最小二乘支持向量机, 预测

Abstract: In order to improve the prediction accuracy of network traffic, this paper proposes a network traffic prediction method based on Ant Colony Optimization（ACO） algorithm and Least Square Support Vector Machine（LSSVM）. In this method, the parameters of LSSVM model are considered as the position vector of ants. Target individuals which lead the ant colony to do global rapid search are determined by dynamic and stochastic extraction, and the optimal ant of this generation searches in small step nearly, lastly, the optimal parameter value is obtained by ACO. The simulation results show that, compared with other network traffic prediction model, the proposed method improves prediction accuracy and can more accurately describe the change rule of network flow.

Key words: network traffic, Ant Colony Optimization（ACO） algorithm, Least Square Support Vector Machine（LSSVM）, prediction