Sunspot activity prediction based on adaptive hybrid algorithms

Abstract

In this paper, by combining the ARIMA model and the BP neural network model, we establish an adaptive hybrid ARIMA-BP neural network model, which provides more accurate results for sunspot prediction. For solar activity prediction, in this paper, based on the multivariate nonlinear regression and BP neural network model, we utilize the differential evolutionary algorithm for model solving and obtain satisfactory hybrid model solving results. These results provide new perspectives and methods for solar activity prediction, and provide useful references and insights for research and practice in related fields.