Related papers: Using the Maximum X-ray Flux Ratio and X-ray Backg…
Solar flare activity is characterised by different classification systems, both in optical and X-ray ranges. The most generally accepted classifications of solar flares describe important parameters of flares such as the maximum of…
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…
To better understand long-term flare activity, we present a statistical study on soft X-ray flares from May 1976 to May 2008. It is found that the smoothed monthly peak fluxes of C-class, M-class, and X-class flares have a very noticeable…
We developed a flare prediction model using machine learning, which is optimized to predict the maximum class of flares occurring in the following 24 h. Machine learning is used to devise algorithms that can learn from and make decisions on…
Solar flare activity in cycle 24 is studied. Satellite observations of x-ray fluxes from GOES-15 and UV emission lines from the SDO/EVE experiment are used. The most powerful flares of cycle 24 in classes X9.3 and X8.2 in September 2017 are…
Solar flares are among the most powerful and dynamic events in the solar system, resulting from the sudden release of magnetic energy stored in the Sun's atmosphere. These energetic bursts of electromagnetic radiation can release up to…
Non-thermal and thermal parameters of 85 solar flares of GOES class B1 to M6 (background subtracted classes A1 to M6) have been compared to each other. The hard X-ray flux has been measured by RHESSI and a spectral fitting provided flux and…
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. Here, we use Geostationary Operational Environmental…
Ways to give medium- and short-term predictions of solar flares are proposed according to the statistical analysis of events during solar cycle 23. On one hand, the time distribution of both C and M class flares shows two main periods of…
We study the energy release process of a set of 51 flares (32 confined, 19 eruptive) ranging from GOES class B3 to X17. We use H$\alpha$ filtergrams from Kanzelh\"ohe Observatory together with SDO HMI and SOHO MDI magnetograms to derive…
Large solar flares occasionally trigger significant space-weather disturbances that affect the technological infrastructures of modern civilization, and therefore require further investigation. Although these solar flares have been…
Solar flares are among the most severe space weather phenomena, and they have the capacity to generate radiation storms and radio disruptions on Earth. The accurate prediction of solar flare events remains a significant challenge, requiring…
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…
In this study we compared the temporal and periodic variations of the Maximum CME Speed Index (MCMESI) and the number of different class (C, M, and X) solar X-Ray flares for the last two solar cycles (Cycle 23 and 24). To obtain the…
The purpose of this work is to search the Yangbajing neutron monitor data obtained between 1998 October and 2000 June for solar neutrons associated with solar flares. Using the onset times of 166 BATSE-detected flares with the GOES peak…
Temporal and spectral characteristics of X-ray emission from 60 flares of intensity $\ge$C class observed by Solar X-ray Spectrometer (SOXS) during 2003-2011 are presented. We analyse the X-ray emission observed in four and three energy…
Solar flares, especially the M- and X-class flares, are often associated with coronal mass ejections (CMEs). They are the most important sources of space weather effects, that can severely impact the near-Earth environment. Thus it is…
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…
We present a database of 3137 solar flare ribbon events corresponding to every flare of GOES class C1.0 and greater within 45 degrees from the central meridian, from April 2010 until April 2016, observed by the \emph{Solar Dynamics…
Around the peaks of substantial flares, bright artifact nearly horizontal saturation streaks (B-streaks) corresponding to the brightest parts of the flare sources appear in the STEREO/EUVI 195 A images. We show that the length of such…