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Neural Network Prediction of solar cycle 24

Authors
  • Ajabshirizadeh, A.
  • Jouzdani, N. Masoumzadeh
  • Abbassi, S.
Type
Published Article
Publication Date
Dec 15, 2010
Submission Date
Dec 15, 2010
Identifiers
DOI: 10.1088/1674-4527/11/4/011
Source
arXiv
License
Yellow
External links

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.

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