Sunspot Forecasting by Using Chaotic Time-series Analysis and NARX Network

Chaotic time-series is a dynamic nonlinear system whose features can not be fully reflected by Linear Regression Model or Static Neural Network. While Nonlinear Autoregressive with eXogenous input includes feedback of network output, therefore, it can better reflect the system’s dynamic feature. Take annual active times of sunspot as an example, after verifying the chaos of sunspot time-series and calculating the series’ embedding dimension and delay, we establish sunspot prediction model with NARX network. The result shows that compared with BP Network and ARIMA Model, NARX network can better predict the chaos.