Related papers: Toward Reliable Benchmarking of Solar Flare Foreca…
Based on several magnetic nonpotentiality parameters obtained from the vector photospheric active region magnetograms obtained with the Solar Magnetic Field Telescope at the Huairou Solar Observing Station over two solar cycles, a machine…
We develop a mixed Long Short Term Memory (LSTM) regression model to predict the maximum solar flare intensity within a 24-hour time window 0$\sim$24, 6$\sim$30, 12$\sim$36 and 24$\sim$48 hours ahead of time using 6, 12, 24 and 48 hours of…
Solar flares emanate from solar active regions hosting complex and strong bipolar magnetic fluxes. Estimating the probability of an active region to flare and defining reliable precursors of intense flares is an extremely challenging task…
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…
Solar flares are intense eruptive events caused by the rapid release of magnetic energy, often impacting Earth's space environment through electromagnetic radiation and high-energy particles. Accurate flare prediction is critical for space…
We present the discovery of a relationship between the maximum ratio of the flare flux (namely, 0.5-4 Ang to the 1-8 Ang flux) and non-flare background (namely, the 1-8 Ang background flux), which clearly separates flares into classes by…
The large (X-ray class > M1) and very large (X-ray class >X1) flares (according to the observations of GOES-15 and Preliminary data from Current Catalog of Flare Events) in solar activity cycle 24 were analyzed. The monthly average values…
We developed a reliable probabilistic solar flare forecasting model using a deep neural network, named Deep Flare Net-Reliable (DeFN-R). The model can predict the maximum classes of flares that occur in the following 24 h after observing…
A Bayesian approach to solar flare prediction has been developed, which uses only the event statistics of flares already observed. The method is simple, objective, and makes few ad hoc assumptions. It is argued that this approach should be…
Solar flares originate from magnetically active regions but not all solar active regions give rise to a flare. Therefore, the challenge of solar flare prediction benefits by an intelligent computational analysis of physics-based properties…
The forecast method introduced by Kors\'os et al.(2014) is generalised from the horizontal magnetic gradient (GM), defined between two opposite polarity spots, to all spots within an appropriately defined region close to the magnetic…
Prediction of solar flares is an important task in solar physics. The occurrence of solar flares is highly dependent on the structure and the topology of solar magnetic fields. A new method for predicting large (M and X class) flares is…
Traditional solar flare forecasting approaches have mostly relied on physics-based or data-driven models using solar magnetograms, treating flare predictions as a point-in-time classification problem. This approach has limitations,…
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…
Solar flares produce radiation which 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 number of published approaches to flare…
Solar energetic particle (SEP) events are one of the most crucial aspects of space weather that require continuous monitoring and forecasting using robust methods. We demonstrate a proof of concept of using a data-driven supervised…
A number of methods of flare prediction rely on classification of physical characteristics of an active region, in particular optical classification of sunspots, and historical rates of flaring for a given classification. However these…
Solar flares are defined as outbursts on the surface of the Sun. They occur when energy accumulated in magnetic fields enclosing solar active regions (ARs) is abruptly expelled. Solar flares and associated coronal mass ejections are sources…
We present a case study of solar flare forecasting by means of metadata feature time series, by treating it as a prominent class-imbalance and temporally coherent problem. Taking full advantage of pre-flare time series in solar active…
Flares are a well-studied aspect of the Sun's magnetic activity. Detecting and classifying solar flares can inform the analysis of contamination caused by stellar flares in exoplanet transmission spectra. In this paper, we present a…