Flare-productive active regions
Strong solar flares and coronal mass ejections, here defined not only as the bursts of
electromagnetic radiation but as the entire process in which magnetic energy is released …
electromagnetic radiation but as the entire process in which magnetic energy is released …
Deep learning based solar flare forecasting model. I. Results for line-of-sight magnetograms
X Huang, H Wang, L Xu, J Liu, R Li… - The Astrophysical …, 2018 - iopscience.iop.org
Solar flares originate from the release of the energy stored in the magnetic field of solar
active regions, the triggering mechanism for these flares, however, remains unknown. For …
active regions, the triggering mechanism for these flares, however, remains unknown. For …
Multivariate time series dataset for space weather data analytics
We introduce and make openly accessible a comprehensive, multivariate time series
(MVTS) dataset extracted from solar photospheric vector magnetograms in Spaceweather …
(MVTS) dataset extracted from solar photospheric vector magnetograms in Spaceweather …
Image processing techniques and feature recognition in solar physics
MJ Aschwanden - Solar Physics, 2010 - Springer
This review presents a comprehensive and systematic overview of image-processing
techniques that are used in automated feature-detection algorithms applied to solar data: i) …
techniques that are used in automated feature-detection algorithms applied to solar data: i) …
Solar flare prediction model with three machine-learning algorithms using ultraviolet brightening and vector magnetograms
N Nishizuka, K Sugiura, Y Kubo, M Den… - The Astrophysical …, 2017 - iopscience.iop.org
We developed a flare prediction model using machine learning, which is optimized to predict
the maximum class of flares occurring in the following 24 hr. Machine learning is used to …
the maximum class of flares occurring in the following 24 hr. Machine learning is used to …
Toward reliable benchmarking of solar flare forecasting methods
Solar flares occur in complex sunspot groups, but it remains unclear how the probability of
producing a flare of a given magnitude relates to the characteristics of the sunspot group …
producing a flare of a given magnitude relates to the characteristics of the sunspot group …
A comparison of flare forecasting methods. I. Results from the “all-clear” workshop
G Barnes, KD Leka, CJ Schrijver, T Colak… - The Astrophysical …, 2016 - iopscience.iop.org
Solar flares produce radiation that can have an almost immediate effect on the near-Earth
environment, making it crucial to forecast flares in order to mitigate their negative effects. The …
environment, making it crucial to forecast flares in order to mitigate their negative effects. The …
Solar flare prediction using advanced feature extraction, machine learning, and feature selection
OW Ahmed, R Qahwaji, T Colak, PA Higgins… - Solar Physics, 2013 - Springer
Novel machine-learning and feature-selection algorithms have been developed to study: i)
the flare-prediction-capability of magnetic feature (MF) properties generated by the recently …
the flare-prediction-capability of magnetic feature (MF) properties generated by the recently …
Operational prediction of solar flares using a transformer-based framework
Solar flares are explosions on the Sun. They happen when energy stored in magnetic fields
around solar active regions (ARs) is suddenly released. Solar flares and accompanied …
around solar active regions (ARs) is suddenly released. Solar flares and accompanied …
A comparison of flare forecasting methods. III. Systematic behaviors of operational solar flare forecasting systems
A workshop was recently held at Nagoya University (2017 October 31–November 2),
sponsored by the Center for International Collaborative Research, at the Institute for Space …
sponsored by the Center for International Collaborative Research, at the Institute for Space …