Vol 11, No 4 (2011) / Ajabshirizadeh

Neural network prediction of solar cycle 24

A. Ajabshirizadeh, N. Masoumzadeh Jouzdani, Shahram Abbassi

Abstract

The ability to predict the future behavior of solar activity has become extremely import due to its effect on the environment near the Earth. 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 (Rz). Several prediction techniques have been applied and have achieved varying degrees of success in the domain of solar activity prediction. We predict a solar index (Rz) in solar cycle 24 by using a 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 them with other suggested predictions.


Keywords


Sun: activity — sunspots — neural networks — prediction

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