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Solar flares are events of intense scientific interest. Although certain solar conditions are known to be associated with flare activity, the exact location and timing of an individual flare on the Sun cannot as yet be predicted with…
One essential component of operational space weather forecasting is the prediction of solar flares. With a multitude of flare forecasting methods now available online it is still unclear which of these methods performs best, and none are…
In this paper, we consider incorporating data associated with the sun's north and south polar field strengths to improve solar flare prediction performance using machine learning models. When used to supplement local data from active…
Solar flares are transient yet dramatic events in the atmosphere of the Sun, during which a vast amount of magnetic energy is liberated. This energy is subsequently transported through the solar atmosphere or into the heliosphere, and…
Accurate solar flare prediction is crucial due to the significant risks that intense solar flares pose to astronauts, space equipment, and satellite communication systems. Our research enhances solar flare prediction by utilizing advanced…
Solar flares are complicated physical phenomena that are observable in a broad range of the electromagnetic spectrum, from radiowaves to $\gamma$-rays. For a more comprehensive understanding of flares, it is necessary to perform a combined…
A test of a new Bayesian approach to solar flare prediction (Wheatland 2004a) is presented. The approach uses the past history of flaring together with phenomenological rules of flare statistics to make a prediction for the probability of…
A phenomenological model is presented for the quantitative description of individual solar cycles' features, such as onset, intensity, evolution, in terms of the number of M and X-class solar flares. The main elements of the model are the…
The output of solar power generation is significantly dependent on the available solar radiation. Thus, with the proliferation of PV generation in the modern power grid, forecasting of solar irradiance is vital for proper operation of the…
Solar flares are the largest energy-release events in the Solar System, allowing us to study fundamental physical phenomena under extreme conditions. Those include magnetic reconnection, particle acceleration, radiation transport, and…
Solar flares result from the rapid conversion of stored magnetic energy within the Sun's corona. These energy releases are associated with coronal magnetic loops, which are rooted in dense photospheric plasma and are passively transported…
In heliophysics research, predicting solar flares is crucial due to their potential to impact both space-based systems and Earth's infrastructure substantially. Magnetic field data from solar active regions, recorded by solar imaging…
Solar energetic particle (SEP) events are one of the most crucial aspects of space weather. Their prediction depends on various factors including the source solar eruptions such as flares and coronal mass ejections (CMEs). The Geostationary…
This study explores the behavior of machine learning-based flare forecasting models deployed in a simulated operational environment. Using Georgia State University's Space Weather Analytics for Solar Flares benchmark dataset (Angryk et al.…
Solar flares are intense bursts of electromagnetic radiation, which occur due to a rapid destabilization and reconnection of the magnetic field. While pre-flare signatures and trends have been investigated from magnetic observations prior…
Improving the performance of solar flare forecasting is a hot topic in solar physics research field. Deep learning has been considered a promising approach to perform solar flare forecasting in recent years. We first used the Generative…
Among the eruptive activity phenomena observed on the Sun, the most technology threatening ones are flares with associated coronal mass ejections (CMEs) and solar energetic particles (SEPs). Flares with associated CMEs and SEPs are produced…
Forecasting future weather and climate is inherently difficult. Machine learning offers new approaches to increase the accuracy and computational efficiency of forecasts, but current methods are unable to accurately model uncertainty in…
Intermittent magnetohydrodynamical turbulence is most likely at work in the magnetized solar atmosphere. As a result, an array of scaling and multi-scaling image-processing techniques can be used to measure the expected self-organization of…
The most powerful explosions on the Sun [...] drive the most severe space-weather storms. Proxy records of flare energies based on SEPs in principle may offer the longest time base to study infrequent large events. We conclude that one…