文献类型：会议论文

英文题名：A High-precision Prediction Model using Ant Colony Algorithm and Neural Network

作者：Li, Dandan[1];Xue, Wanxin[1];Pei, Yilei[1]

第一作者：李丹丹

通讯作者：Li, DD[1]

机构：[1]Beijing Union Univ, Coll Management, Beijing, Peoples R China

第一机构：北京联合大学管理学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Management, Beijing, Peoples R China.|[1141755]北京联合大学管理学院;[11417]北京联合大学;

会议论文集：International Conference on Logistics, Informatics and Service Sciences (LISS)

会议日期：JUL 27-29, 2015

会议地点：Beijing Jiaotong Univ, Int Ctr Informat Res, Barcelona, SPAIN

主办单位：Beijing Jiaotong Univ, Int Ctr Informat Res

语种：英文

外文关键词：cognitive networks; ant colony algorithm; neural network; network traffic prediction

摘要：The concept of Cognitive Network has been proposed and studied, because of the the development of the network technology. Cognitive networks can perceive the external environment; intelligently and automatically change its behavior to adapt the environment. This feature is more suitable to provide security for users with Quality of Service. This paper proposes a hybrid traffic prediction model, which trains BPNN with Ant Colony Algorithm based on the analysis of the present models. Furthermore, the model includes three stages, and the model predicts the network traffic with the hybrid model. The proposed model can avoid the problem of slow convergence speed and an easy trap in local optimum when coming up with a fluctuated network flow. Thus, the traffic prediction with high-precision in cognitive networks is achieved.