Application of Genetic Algorithm and RBF Neural Network in Network Flow Prediction

被引:0
|
作者
Ming, Zhang Ya [1 ]
Bin, Zhang Yu [2 ]
Zhong, Lin Li [3 ]
机构
[1] ShiJiaZhuang Infonnat Engn Vocat Coll, Shijiazhuang, Peoples R China
[2] HeBei Vocat Art Coll, Shijiazhuang, Peoples R China
[3] ShiJiaZhuang Coll, Shijiazhuang, Peoples R China
关键词
network flow; RBF neural network; genetic algorithm; time series prediction;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Time series forecasting is the main method in network flow prediction. RBF neural network is capable of universal approximation, which not only has fast training velocity, but also can solve the local minima problem. Thus, network flow prediction technology based on genetic algorithm and RBF neural network is presented in the paper. And the training parameters are adjusted by genetic algorithm. Network flow data about 40 points can be applied to study the superiority of genetic algorithm and RBF neural network neural network compared with normal RBF neural network. By the analysis of application case, it can be seen that the forecasting performance of genetic algorithm and RBF neural network is better than that of normal RBF neural network.
引用
收藏
页码:298 / 301
页数:4
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