[HTML][HTML] Prediction of solar energetic events impacting space weather conditions
Aiming to assess the progress and current challenges on the formidable problem of the
prediction of solar energetic events since the COSPAR/International Living With a Star …
prediction of solar energetic events since the COSPAR/International Living With a Star …
Short-term solar eruptive activity prediction models based on machine learning approaches: A review
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 …
solar proton events (SPE), have an important impact on space weather and our …
Physics-driven machine learning for the prediction of coronal mass ejections' travel times
Abstract Coronal Mass Ejections (CMEs) correspond to dramatic expulsions of plasma and
magnetic field from the solar corona into the heliosphere. CMEs are scientifically relevant …
magnetic field from the solar corona into the heliosphere. CMEs are scientifically relevant …
Prediction of severe thunderstorm events with ensemble deep learning and radar data
S Guastavino, M Piana, M Tizzi, F Cassola, A Iengo… - Scientific Reports, 2022 - nature.com
The problem of nowcasting extreme weather events can be addressed by applying either
numerical methods for the solution of dynamic model equations or data-driven artificial …
numerical methods for the solution of dynamic model equations or data-driven artificial …
Operational solar flare forecasting via video-based deep learning
Operational flare forecasting aims at providing predictions that can be used to make
decisions, typically on a daily scale, about the space weather impacts of flare occurrence …
decisions, typically on a daily scale, about the space weather impacts of flare occurrence …
Probabilistic solar flare forecasting using historical magnetogram data
K van der Sande, A Muñoz-Jaramillo… - The Astrophysical …, 2023 - iopscience.iop.org
Solar flare forecasting research using machine learning (ML) has focused on high-resolution
magnetogram data from the SDO/HMI era covering solar cycle 24 and the start of solar cycle …
magnetogram data from the SDO/HMI era covering solar cycle 24 and the start of solar cycle …
Deep neural networks of solar flare forecasting for complex active regions
M Li, Y Cui, B Luo, J Wang, X Wang - Frontiers in Astronomy and …, 2023 - frontiersin.org
Solar flare forecasting is one of major components of operational space weather forecasting.
Complex active regions (ARs) are the main source producing major flares, but only a few …
Complex active regions (ARs) are the main source producing major flares, but only a few …
[HTML][HTML] Efficient identification of pre-flare features in SDO/AIA images through use of spatial Fourier transforms
In this “Methods” paper, we investigate how to compress SDO/AIA data by transforming the
AIA source maps into the Fourier domain at a limited set of spatial frequency points …
AIA source maps into the Fourier domain at a limited set of spatial frequency points …
Can Solar Limb Flare Prediction Be Properly Made by Extreme-ultraviolet Intensities?
We address the question of whether the solar limb flare prediction can be properly made by
EUV intensity, which has less projection effects than solar white light and magnetogram …
EUV intensity, which has less projection effects than solar white light and magnetogram …
A Strong-flare Prediction Model Developed Using a Machine-learning Algorithm Based on the Video Data Sets of the Solar Magnetic Field of Active Regions
J Wang, B Luo, S Liu, Y Zhang - The Astrophysical Journal …, 2023 - iopscience.iop.org
It is well accepted that the physical properties obtained from the solar magnetic field
observations of active regions (ARs) are related to solar eruptions. These properties consist …
observations of active regions (ARs) are related to solar eruptions. These properties consist …