Related papers: Solar Active Regions Emergence Prediction Using Lo…
High radio frequencies observations with the Italian network of large single-dish radio telescopes resulted in ~450 solar images between 2018 and 2023 in K-band frequency range (18-26 GHz). Solar radio mapping at these frequencies allows…
Solar active regions (ARs) that produce strong flares and coronal mass ejections (CMEs) are known to have a relatively high non-potentiality and are characterized by delta-sunspots and sheared magnetic structures. In this study, we conduct…
Global-scale energy flow throughout Earth's magnetosphere (MSP) is catalyzed by processes that occur at Earth's magnetopause (MP). Magnetic reconnection is one process responsible for solar wind entry into and global convection within the…
The spatial inhomogeneity of the distribution of coronal mass ejection (CME) occurrences in the solar atmosphere could provide a tool to estimate the longitudinal position of the most probable CME-capable active regions in the Sun. The…
There is a lack of research on the analysis of per-user traffic in cellular networks, for deriving and following traffic-aware network management. \textcolor{black}{In fact, the legacy design approach, in which resource provisioning and…
Modeling brain dynamics to better understand and control complex behaviors underlying various cognitive brain functions are of interests to engineers, mathematicians, and physicists from the last several decades. With a motivation of…
Demand forecasting in power sector has become an important part of modern demand management and response systems with the rise of smart metering enabled grids. Long Short-Term Memory (LSTM) shows promising results in predicting time series…
Large scale solar eruptions significantly impact space weather and damages space-based human infrastructures. It is necessary to predict large scale solar eruptions, which will enable us to protect our vulnerable infrastructures of modern…
Solar flares are caused by magnetic eruptions in active regions (ARs) on the surface of the sun. These events can have significant impacts on human activity, many of which can be mitigated with enough advance warning from good forecasts. To…
In this paper, we introduce a novel methodology for leveraging shape-based characteristics of magnetograms of active region (AR) patches and provide a novel capability for predicting solar flares covering the entirety of the solar disk (AR…
We discuss a prediction of the solar activity on a short time-scale applying the method based on a combination of a nonlinear mean-field dynamo model and the artificial neural network. The artificial neural network which serves as a…
We attempt to forecast M-and X-class solar flares using a machine-learning algorithm, called Support Vector Machine (SVM), and four years of data from the Solar Dynamics Observatory's Helioseismic and Magnetic Imager, the first instrument…
Active regions are the source of the majority of magnetic flux rope ejections that become Coronal Mass Ejections (CMEs). To identify in advance which active regions will produce an ejection is key for both space weather prediction tools and…
Using a recently suggested magneto-morphological classification (MMC, Abramenko, 2021, MNRAS Vol 507) of solar active regions (ARs), we explored 3048 ARs, observed from12 May 1996 to 27 December 2021. Magnetograms were acquired with the…
Among several heliophysical and geophysical quantities, the accurate evolution of the solar irradiance is fundamental to forecast the evolution of the neutral and ionized components of the Earth's atmosphere.We developed an artificial…
A statistical study of 77 solar active regions (ARs) is conducted to investigate the existence of identifiable correlations between the subsurface structural disturbances and the activity level of the active regions. The disturbances…
The sudden release of magnetic energy on the Sun drives powerful solar flares and coronal mass ejections. The key issue is the difficulty in predicting the occurrence time and location of strong solar eruptions, i.e., those leading to the…
The coronal magnetic field evolution of 20 bipolar active regions (ARs) is simulated from their emergence to decay using the time-dependent nonlinear force-free field method of Mackay et al. A time sequence of cleaned photospheric…
We present a method for performing data-driven simulations of solar active region formation and evolution. The approach is based on magnetofriction, which evolves the induction equation assuming the plasma velocity is proportional to the…
Here, we developed a complex network of solar active regions (ARs) to study various local and global properties of the network. The values of the Hurst exponent ($0.8-0.9$) were evaluated by both the detrended fluctuation analysis and the…