| Presentation | 2012-04-12 Forecasting individual trends using resolution adaptive arima Hiroki NAKAYAMA, Shingo ATA, Ikuo OKA, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Analyzing and predicting the time series of traffic trends is important in the perspective of network operation and management. However, it is difficult to accurately predict traffic trends because this strongly depends on the time, the type of content, and its popularity. We propose a new method based on wavelet transform and the auto regressive integrated moving average (ARIMA) model to predict traffic trends more accurately. We first demonstrate that applying a wavelet transform can improve the accuracy of prediction compared to the original ARIMA model; however, it still has large error due to the fixed time granularity of each resolution. We therefore propose a resolution adaptive ARIMA (RA-ARIMA) model which is based on dynamic time granularity and a Wavelet-ARIMA model. We demonstrate that by applying it to the real monitored data in a major P2P file-sharing system the mean squared error and normalized mean squared error of RA-ARIMA can be reduced by more than 80% of that of Wavelet-ARIMA. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Demand-Prediction / Wavelet Transform / Time Series Analysis / ARIMA Models |
| Paper # | IN2012-1 |
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| Conference Information | |
| Committee | IN |
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| Conference Date | 2012/4/5(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Information Networks (IN) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Forecasting individual trends using resolution adaptive arima |
| Sub Title (in English) | |
| Keyword(1) | Demand-Prediction |
| Keyword(2) | Wavelet Transform |
| Keyword(3) | Time Series Analysis |
| Keyword(4) | ARIMA Models |
| 1st Author's Name | Hiroki NAKAYAMA |
| 1st Author's Affiliation | Graduate School of Engineering, Osaka City University() |
| 2nd Author's Name | Shingo ATA |
| 2nd Author's Affiliation | Graduate School of Engineering, Osaka City University |
| 3rd Author's Name | Ikuo OKA |
| 3rd Author's Affiliation | Graduate School of Engineering, Osaka City University |
| Date | 2012-04-12 |
| Paper # | IN2012-1 |
| Volume (vol) | vol.112 |
| Number (no) | 4 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |