Solar flare prediction using highly stressed longitudinal magnetic field parameters
Solar flare prediction using highly stressed longitudinal magnetic field parameters
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DOI：
10.1088/1674-4527/13/3/010
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发表时间：
2013-01
影响因子：
1.8
通讯作者：
Xin Huang;Huaning Wang
中科院分区：
文献类型：
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作者：
Xin Huang;Huaning Wang
从SOHO/MDI磁象图中提取了3个新的纵向磁场参数来表征活动区应力磁场的性质，并计算了1055个活动区的耀斑产率。我们发现，建议的参数可以用来区分燃烧的样本从非燃烧的样本。利用长期积累的MDI数据，采用数据挖掘方法建立太阳耀斑预测模型。此外，决策边界，这是用来区分燃烧和非燃烧的样本，是由决策树算法确定。最后，通过10折交叉验证技术对预测模型的性能进行了评估。我们的结论是，一个有效的太阳耀斑预测模型可以建立一个建议的纵向磁场参数与数据挖掘方法。
Three new longitudinal magnetic field parameters are extracted from SOHO/MDI magnetograms to characterize properties of the stressed magnetic field in active regions, and their flare productivities are calculated for 1055 active regions. We find that the proposed parameters can be used to distinguish flaring samples from non-flaring samples. Using the long-term accumulated MDI data, we build the solar flare prediction model by using a data mining method. Furthermore, the decision boundary, which is used to divide flaring from non-flaring samples, is determined by the decision tree algorithm. Finally, the performance of the prediction model is evaluated by 10-fold cross validation technology. We conclude that an efficient solar flare prediction model can be built by the proposed longitudinal magnetic field parameters with the data mining method.