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arXiv 1504.00294astro-ph.SRphysics.space-ph
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利用最大X射线通量比和X射线背景预测太阳耀斑级

Using the Maximum X-ray Flux Ratio and X-ray Background to Predict Solar Flare Class

Lisa M. Winter, K. Balasubramaniam

摘要:

我们提出的耀斑通量(即,0.5-4 Ang的1-8 Ang的流量)和非耀斑背景(即,1-8 Ang的背景流量)的最大比率之间的关系的发现,这清楚地分离耀斑到类的峰值通量水平。我们建立了这种关系的基础上分析的地球同步运行环境卫星(GOES)X射线观测的~ 50,000 X,M,C,B耀斑来自NOAA/SWPC耀斑目录。采用机器学习技术(K-最近邻和最近质心算法)的组合,我们显示了不同的峰值耀斑能量的观测参数的分离。通过对第22-23周太阳耀斑参数提取的训练,成功地预测了第24周X级耀斑100%、M级耀斑76%、C级耀斑80%和B级耀斑81%的耀斑类别,验证了该分析的正确性。

英文摘要:

We present the discovery of a relationship between the maximum ratio of the flare flux (namely, 0.5-4 Ang to the 1-8 Ang flux) and non-flare background (namely, the 1-8 Ang background flux), which clearly separates flares into classes by peak flux level. We established this relationship based on an analysis of the Geostationary Operational Environmental Satellites (GOES) X-ray observations of ~ 50,000 X, M, C, and B flares derived from the NOAA/SWPC flares catalog. Employing a combination of machine learning techniques (K-nearest neighbors and nearest-centroid algorithms) we show a separation of the observed parameters for the different peak flaring energies. This analysis is validated by successfully predicting the flare classes for 100% of the X-class flares, 76% of the M-class flares, 80% of the C-class flares and 81% of the B-class flares for solar cycle 24, based on the training of the parametric extracts for solar flares in cycles 22-23.

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