基于小波分解的某些非平稳时间序列预测方法

提出一种时间序列预测方法,称为小波预测方法.通过小波分解可以将某些非平稳时间序列分解成多层近似意义上的平稳时间序列,然后采用自回归模型对分解后的时间序列进行预测,从而得到原始时间序列的预测值.对年平均太阳黑子数的预测结果表明,该方法比传统的时间序列预测方法和神经网络预测方法的预测精度高,可以很好地应用于某些非平稳时间序列的预测中.

Forecasting of Some Non-Stationary Time Series Based on Wavelet Decomposition

A forecasting method of time series called wavelet-domain predictor is proposed.Some non-stationary time series can be decomposed into several approximate stationary time series with wavelet decomposition.Decomposed time series are forecasted with auto-regression model,to obtain forecasting results of the original time series.Experiments with sunspot activity data show that the method is better than traditional forecasting approaches and neural network approaches,and can be applied to forecasting of some non-stationary time series effectively.