行星际日冕物质抛射地磁效应研究的支持向量机方法初步研究

Study on Geoeffectiveness of Interplanetary Coronal Mass Ejections by Support Vector Machine

行星际日冕物质抛射(Interplanetary Coronal Mass Ejection, ICME)与地球磁层相互作用并带来地磁暴等地磁扰动.从Richardson和Cane提供的近地球ICME列表中筛选出ICME事件集,基于ICME扰动期间的行星际等离子体与磁场数据提取出特征.通过计算各特征的费舍尔分值(Fisher Score),对这些特征进行选择,发现行星际磁场南北向分量持续时间小于-10nT且激波等扰动所带来的ICME扰动开始时,太阳风速度的增量等特征与ICME事件的地磁效应密切相关.这与现有的传统统计研究结果一致.以这些特征为基础,训练得到的径向基函数支持向量机能够以0.78±0.08的准确率判断ICME事件是否会产生中等及以上强度的地磁暴(Dst≤-50nT).

As arriving at the Earth, Interplanetary Coronal Mass Ejections(ICME) will interact with the Earth’s magnetosphere and cause geomagnetic storms. The ICME event set is obtained by Richardson and Cane’s Near Earth ICME list, and the input features are extracted based on interplanetary solar wind and magnetic data during ICME disturbance. A total of 483 ICME events from 1996 to 2006 are chosen in this study. 13 magnetic and kinetic features are finally selected for the training of the machine learning model. Rank of each feature’s Fisher score indicates that the duration of the south-directed interplanetary magnetic field that is larger than 10 nT and the increase of solar wind speed at the upstream shock or wave disturbance is closely related to the geoeffectiveness of ICME events, which is consistent with those former statistical results. The trained Radial Basis Function Support Vector Machine(RBF-SVM) can determine whether an ICME event could trigger moderate or stronger geomagnetic storms(Dst ≤-50 nT) effectively with an accuracy of 0.78±0.08.The results show that RBF-SVM can be used as a powerful tool in further analysis, and the better prediction of the geoeffectiveness of ICME will be obtained.