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Paper   IPM / Astronomy / 11811
School of Astronomy
  Title:   Neural network prediction of solar cycle 24
1.  A. Ajabshirizadeh
2.  N. Masoomzadeh
3.  Sh. Abbassi
  Status:   Published
  Journal: Research in Astron. Astrophys.
  No.:  4
  Vol.:  11
  Year:  2011
  Pages:   491?496
  Publisher(s):   Research in Astronomy and astrophysics 2011
  Supported by:            IPM IPM
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 ($R_z$), \textbf{ and 10.7-cm solar radio flux index ($F_{10.7}$)}. 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 some solar indices ($R_z$, \textbf{$F_{10.7}$}) 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 \textbf{ and yearly solar radio flux,} 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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