Machine learning in solar physics
A Asensio Ramos, MCM Cheung, I Chifu… - Living Reviews in Solar …, 2023 - Springer
The application of machine learning in solar physics has the potential to greatly enhance our
understanding of the complex processes that take place in the atmosphere of the Sun. By …
understanding of the complex processes that take place in the atmosphere of the Sun. By …
Machine learning in solar physics
The application of machine learning in solar physics has the potential to greatly enhance our
understanding of the complex processes that take place in the atmosphere of the Sun. By …
understanding of the complex processes that take place in the atmosphere of the Sun. By …
[HTML][HTML] Heliophysics and space weather information architecture and innovative solutions: current status and ways forward
Over the past 10 years, a paradigm shift has happened in the world of science and
information technology. Open science is becoming the de facto standard, as underlined by …
information technology. Open science is becoming the de facto standard, as underlined by …
Improving the electron radiation belt nowcast and forecast using the SafeSpace data assimilation modeling pipeline
A Brunet, N Dahmen, C Katsavrias, O Santolík… - Space …, 2023 - Wiley Online Library
The H2020 SafeSpace project aims at the implementation of a space weather safety
prototype, in particular to predict the deep charging hazard. The proposed service is built on …
prototype, in particular to predict the deep charging hazard. The proposed service is built on …
A New Method for Predicting Non‐Recurrent Geomagnetic Storms
C Wang, Q Ye, F He, B Chen, X Zhang - Space Weather, 2023 - Wiley Online Library
Predicting non‐recurrent geomagnetic storms caused by Coronal Mass Ejection (CME) is
important and necessary for space weather forecasting. Previous studies have shown that it …
important and necessary for space weather forecasting. Previous studies have shown that it …
基于神经网络的未来3天Kp指数预报建模与可解释AI应用
王听雨， 罗冰显， 陈艳红， 石育榕， 王晶晶， 刘四清 - 空间科学学报, 2024 - cjss.ac.cn
当前业务中对未来3 天Kp 指数预报需求强烈. 但地磁暴中多参数耦合导致难以量化各预报因子
对Kp 值的贡献, 制约了预报精度提升. 本文构建了神经网络3 天Kp 指数预报模型 …
对Kp 值的贡献, 制约了预报精度提升. 本文构建了神经网络3 天Kp 指数预报模型 …
[PDF][PDF] 基于神经网络的未来3 天Kp 指数预报建模与可解释AI 应用初探
王听雨， 罗冰显， 陈艳红， 石育榕， 王晶晶， 刘四清 - 空间科学学报 - researchgate.net
摘要当前业务中对未来3 天Kp 指数预报需求强烈. 但地磁暴中多参数耦合导致难以量化各预报
因子对Kp 值的贡献, 制约了预报精度提升. 本文构建了神经网络3 天Kp 指数预报模型, 并使用AI …
因子对Kp 值的贡献, 制约了预报精度提升. 本文构建了神经网络3 天Kp 指数预报模型, 并使用AI …
[PDF][PDF] DETECTION OF GEOMAGNETIC STORM SUDDEN COMMENCEMENTS WITH THE USE OF NEURAL NETWORK ARCHITECTURES
T VOLOSHIN, K ZAYTSEV - Journal of Theoretical and Applied Information …, 2024 - jatit.org
The purpose of the study is to examine various options to address the task of detecting the
starting stage of geomagnetic storms, storm sudden commencement (SSC or SC), based on …
starting stage of geomagnetic storms, storm sudden commencement (SSC or SC), based on …