Multiresolution Analysis and Forecasting of Mobile Communication Traffic

Combined with Fourier spectrum prior knowledge, a novel wavelet multiresolution analysis and forecasting algorithm is proposed. It focuses on long term trend prediction of multi-periodic, non-stationary, mobile communication traffic series. New algorithm calculates the Fourier spectrum for multi-per...

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Bibliographic Details
Published in:电子学报：英文版 2013-04, Vol.22 (2), p.373-376
Main Author: PENG Yu LEI Miao GUO Jia PENG Xiyuan
Format: Article
Language:English
Subjects:
交通数据
傅立叶频谱
先验知识
周期分量
小波多分辨率分析
移动通信
话务量
预测算法
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Summary:Combined with Fourier spectrum prior knowledge, a novel wavelet multiresolution analysis and forecasting algorithm is proposed. It focuses on long term trend prediction of multi-periodic, non-stationary, mobile communication traffic series. New algorithm calculates the Fourier spectrum for multi-periodic series at first, and takes the prominent period components with definite phys- ical notion as the prior knowledge. After that, it extracts more valuable time domain features with wavelet multires- olution analysis. Finally, it adopts a single model to predict each of them, and integrates the prediction results to gain the final trend prediction of traffic time series. Experi- mental results on real traffic data show that all isolated components in proposed multiresolution analysis deliver the distinct physical information in traffic data. Addition- ally, our algorithm can pick out most of prominent period components revealed in the Fourier spectrum and improve prediction accuracy.
ISSN:1022-4653