Composite Forecasting Model of Sunspot Time Sequences Based on EMD
According to the complexity of sunspots, this paper uses Empirical Mode Decomposition(EMD) method, the solar activity contains all of the time scale changes separated into the inherent weight smooth Intrinsic Mode Function(IMF) and remainders. It observes each component of the spectrum, based on the characteristics of the low frequency IMF component selection Auto-regressive Moving Average(ARMA) model predicted the average directly, and the high frequency IMF using neural network forecast. Through the various components of the primary signal reconstruction predicts a prediction sequence, and increases the prediction accuracy. Simulation results show that the model has higher forecast accuracy.
国家科技期刊平台
NSTL
万方数据
维普
