Neural Network Prediction of solar cycle 24

TL;DR

This paper employs neural networks to predict the amplitude and timing of solar cycle 24, estimating a peak in 2013 with a sunspot number of 65, aiding space weather forecasting.

Contribution

It introduces a neural network approach to predict solar activity indices, providing specific forecasts for solar cycle 24's peak timing and intensity.

Findings

Cycle 24 peak in 2013 with sunspot number 65

Neural network effectively analyzes solar activity time series

Predictions compared with other models

Abstract

The ability to predict the future behavior of solar activity has become of extreme importance due to its effect on the near Earth environment. Predictions of both the amplitude and timing of the next solar cycle will assist in estimating the various consequences of Space Weather. The level of solar activity is usually expressed by international sunspot number ($R_z$). Several prediction techniques have been applied and have achieved varying degrees of success in the domain of solar activity prediction. In this paper, we predict a solar index ($R_z$) in solar cycle 24 by using the neural network method. The neural network technique is used to analyze the time series of solar activity. According to our predictions of yearly sunspot number, the maximum of cycle 24 will occur in the year 2013 and will have an annual mean sunspot number of 65. Finally, we discuss our results in order to compare it with other suggested predictions.