Time series forecasting based on wavelet filtering

作者：

Highlights：

• The study proposes a forecasting method based on wavelet filtering.

• The proposed method analyzes time series in both the time and frequency domains.

• The proposed method decomposes the time series into the trend and variation parts.

• Simulation and real data demonstrated the applicability of the proposed method.

摘要

•The study proposes a forecasting method based on wavelet filtering.•The proposed method analyzes time series in both the time and frequency domains.•The proposed method decomposes the time series into the trend and variation parts.•Simulation and real data demonstrated the applicability of the proposed method.

论文关键词：ARIMA,Forecasting,Time series,Wavelet transforms

论文评审过程：Available online 20 January 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.01.026