Name
Abstract | ||
|---|---|---|
The traditional network traffic prediction is based on the establishment of a linear model, which can't describe the changes of network traffic accurately, resulting in low prediction accuracy. This paper proposes a new model of network traffic prediction based on wavelet transform and Genetic Algorithm. Firstly, after a wavelet decomposition, network traffic is turned into many stable components. Secondly, using BP neural network to predict each stable component, and optimizing neural network by genetic algorithm. Finally, all the prediction of components is combined to achieve highly-accurate traffic prediction. The experimental results show that the model has a better predictive effect. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-74521-3_22 | HUMAN CENTERED COMPUTING, HCC 2017 |
Keywords | Field | DocType |
BP neural network, Wavelet transform, Network traffic prediction, Time series, Genetic algorithms | Wavelet decomposition,Pattern recognition,Linear model,Computer science,Artificial intelligence,Traffic prediction,Artificial neural network,Genetic algorithm,Wavelet transform | Conference |
Volume | ISSN | Citations |
10745 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuehui Zhao | 1 | 0 | 0.34 |
| Wanbo Zheng | 2 | 0 | 0.68 |
| Lei Ding | 3 | 142 | 26.77 |
| Xingang Zhang | 4 | 0 | 0.34 |