利用概率模型研究长期太阳黑子和K指数几何周期

Danish Hassan, Hamza Khan, M. F. Akhter, Muhammad Danish Khan, Shaheen Abbas
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引用次数: 0

摘要

本文所做的研究工作包括应用不同的众所周知的概率分布模型。这包括利用总数据了解24个太阳黑子周期的行为和动力学。时间序列数据集选自1749年至2014年。为了观察太阳活动对K指数活动的影响,研究中还纳入了1932年至2014年的双周期。这项比较研究有助于观察长期的日地联系。太阳的磁场在周期的每11年后就会发生极性反转。因此,每隔22年,北极就会再次成为北极。利用著名的Kolmogorov-Smirnov检验(KST)和Anderson-DDarling检验(ADT),得到了每个太阳黑子周期的概率分布模型,并进行了比较。得到了所有太阳黑子周期的显著概率模型。在选定的数据集上拟合的概率分布模型可能有助于了解太阳和地磁活动的趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A STUDY OF LONG-TERM SUNSPOTS AND K-INDEX GEOMETRIC CYCLES USING PROBABILISTIC MODELING
The research work done in this paper comprises the application of different well-known probability distribution models. This includes the understanding of the behavior and dynamics of 24 sunspot cycles with total data. The time-series data sets were selected from 1749 to 2014. To observe the solar activity effects on K-index activity the double cycles from 1932 to 2014 were also incorporated in the study. The comparative study is useful to observe the long-term solar-terrestrial connection. The magnetic field of the sun reverses its polarity after every 11 years of the cycle. So after every 22 years, the north pole becomes again north pole. By using the two well-known tests Kolmogorov-Smirnov (KST) and Anderson-Darling test (ADT) the probability distribution models were obtained for each sunspot cycles and compare. The significant probability models for all the sunspot cycles have been obtained. The fitted probability distribution models on selected data sets may be useful to understand the trend of solar and geomagnetic activity.
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