Author Details

Affiliations
1 Department of Physics, Presidency College, Chennai, IN
2 Department of Physics, Dhanalakshmi Srinivasan College of Engineering and Technology, Chennai, IN

Source

Research Journal of Science and Technology, Vol 3, No 1 (2011), Pagination: 26-28

Abstract

The study of solar activity and solar terrestrial relations, the sunspot number has always been taken as the main indicator of the intensity of solar activity. Various new techniques like neural networks, learning nonlinear dynamics and others are used by researchers to predict solar activity. But we are yet to obtain reasonably good results. This is mainly because the reason of the variation of solar activity is still unknown. Hence it is important to analyze the characteristics of the data. This paper considers sunspot as the index of solar activity and fractal analysis is used to examine the predictability of solar activity. For the period 1994 to 2008, the average fractal dimension for periods of 10 days or less was about 1.49. But during the same period, the average fractal dimension was 1.92 for periods longer than 10 days. Hence the result is encouraging for short-term prediction (i.e.) within about 10 days, but discouraging for medium-term prediction ( longer than 10 days ).

Keywords

Solar Activity, Neural Networks, Nonlinear Dynamics, Fractal Analysis, Fractal Dimension.

Full Text

Username
Password
Remember me