太阳耀斑预测的两阶段层次框架

IF 8.6 1区 物理与天体物理 Q1 ASTRONOMY & ASTROPHYSICS
Hao Deng, Yuting Zhong, Hong Chen, Jun Chen, Jingjing Wang, Yanhong Chen, Bingxian Luo
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引用次数: 0

摘要

摘要太阳耀斑通常伴随着日冕物质抛射等太阳现象,是影响空间天气的重要来源之一。研究太阳耀斑的预报方法对减轻其对地球的破坏性影响具有重要意义。对2010 - 2017年太阳动力学观测站日震磁成像仪采集的空间气象HMI活动区斑块(SHARPs)数据进行统计分析,发现两类太阳耀斑活动区(ARs)的分布存在差异。为了更好地利用这种内在分布信息,提出了一种两阶段分层预测框架。特别地,我们通过平衡随机森林和朴素贝叶斯方法将未来48小时内至少发生一次太阳耀斑事件的耀斑事件作为耀斑事件,然后通过学习模型的级联模块预测耀斑事件。对2016 - 2019年SHARPs数据的实证评估验证了我们的框架的良好性能,如真技能统计量为0.727。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two-stage Hierarchical Framework for Solar Flare Prediction
Abstract Solar flares, often accompanied by coronal mass ejections and other solar phenomena, are one of the most important sources affecting space weather. It is important to investigate the forecast approach of solar flares to mitigate their destructive effect on the Earth. Statistical analysis, associated with data from 2010 to 2017 in Space-weather HMI Active Region Patches (SHARPs) collected by the Solar Dynamics Observatory's Helioseismic and Magnetic Imager, reveals that there is a distribution divergence between the two types of active regions (ARs) of solar flares. A two-stage hierarchical prediction framework is formulated to better utilize this intrinsic distribution information. Specially, we pick up the ARs where at least one solar flare event occurs within the next 48 hr as flaring ARs through balanced random forest and naive Bayesian methods and then predict the events from flaring ARs by a cascade module of learning models. The empirical evaluation of SHARPs data from 2016 to 2019 verifies the promising performance of our framework, e.g., 0.727 for the true skill statistic.
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来源期刊
Astrophysical Journal Supplement Series
Astrophysical Journal Supplement Series 地学天文-天文与天体物理
CiteScore
14.50
自引率
5.70%
发文量
264
审稿时长
2 months
期刊介绍: The Astrophysical Journal Supplement (ApJS) serves as an open-access journal that publishes significant articles featuring extensive data or calculations in the field of astrophysics. It also facilitates Special Issues, presenting thematically related papers simultaneously in a single volume.
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