Data Mining of Time Series Based on Wavelet Analysis
Tong Wei-min, Yijun Li, Shan Yong-zheng · Jisuanji gongcheng · 2008
This paper presents wavelet method and ARMA model for time series data mining.According to the wavelet denoising and wavelet decomposition,the hidden period and the nonstationarity existed in financial time series are extracted and separated by wavelet transformation.The characteristic of wavelet decomposition series is applied to BP networks and an Autoregressive Moving Average(ARMA) model.Finally,wavelet reconstruction is used to realize time series forcaseting.It shows that the proposed method can provide more accurate results.