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Short-term solar eruptive activity prediction models based on machine learning approaches:A review
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作者 Xin HUANG Zhongrui ZHAO +3 位作者 Yufeng ZHONG Long XU Marianna B.KORSÓS R.ERDÉLYI 《Science China Earth Sciences》 SCIE EI CAS 2024年第12期3727-3764,共38页
Solar eruptive activities,mainly including solar flares,coronal mass ejections(CME),and solar proton events(SPE),have an important impact on space weather and our technosphere.The short-term solar eruptive activity pr... Solar eruptive activities,mainly including solar flares,coronal mass ejections(CME),and solar proton events(SPE),have an important impact on space weather and our technosphere.The short-term solar eruptive activity prediction is an active field of research in the space weather prediction.Numerical,statistical,and machine learning methods are proposed to build prediction models of the solar eruptive activities.With the development of space-based and ground-based facilities,a large amount of observational data of the Sun is accumulated,and data-driven prediction models of solar eruptive activities have made a significant progress.In this review,we briefly introduce the machine learning algorithms applied in solar eruptive activity prediction,summarize the prediction modeling process,overview the progress made in the field of solar eruptive activity prediction model,and look forward to the possible directions in the future. 展开更多
关键词 Solar flare Coronal mass ejection Solar proton event Machine learning Prediction model
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