Name
Abstract | ||
|---|---|---|
To deal with the characteristic of network traffic, a prediction algorithm based on wavelet transform and Season ARIMA model is introduced in this paper. The complex correlation structure of the network history traffic is exploited with wavelet method .For the traffic series under different time scale, self-similarity is analyzed and different prediction model is selected for predicting. The result series is reconstructed with wavelet method. Simulation results show that the proposed method can achieve higher prediction accuracy rather than single prediction model. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-21111-9_17 | ISNN (3) |
Keywords | Field | DocType |
single prediction model,different prediction model,higher prediction accuracy,network traffic prediction,network traffic,network history traffic,season arima model,traffic series,prediction algorithm,wavelet method,wavelet transform,prediction model,arima model,seasonality | Pattern recognition,Computer science,Autoregressive integrated moving average,Artificial intelligence,Traffic prediction,Wavelet transform,Wavelet | Conference |
Volume | ISSN | Citations |
6677 | 0302-9743 | 2 |
PageRank | References | Authors |
0.44 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongtao Wei | 1 | 2 | 0.44 |
| jinkuan wang | 2 | 94 | 33.64 |
| Cuirong Wang | 3 | 110 | 15.54 |