Related papers: Forecasting Solar Cycle 25 using Deep Neural Netwo…
Solar radiation prediction is an important challenge for the electrical engineer because it is used to estimate the power developed by commercial photovoltaic modules. This paper deals with the problem of solar radiation prediction based on…
Whether the upcoming cycle 24 of solar activity will be strong or not is being hotly debated. The solar cycle is produced by a complex dynamo mechanism. We model the last few solar cycles by `feeding' observational data of the Sun's polar…
Sunspots have been observed for over four centuries and the magnetic nature of sunspot cycles has been known for about a century; however, some of its underlying physics still remain elusive. It is known that the solar magnetic cycle…
Machine learning techniques have been widely used in attempts to forecast several solar datasets. Most of these approaches employ supervised machine learning algorithms which are, in general, very data hungry. This hampers the attempts to…
In addition to the Gnevyshev-Ohl rule (GOR), the relation of the odd cycle with the subsequent even one in the 22-year Hale solar cycle was found. It is shown that 3 years before the 11-year minimum $m$, the value of the relative sunspot…
Solar radio flux along with geomagnetic indices are important indicators of solar activity and its effects. Extreme solar events such as flares and geomagnetic storms can negatively affect the space environment including satellites in…
We present a comprehensive analysis of Solar Cycle 25 aimed at precisely constraining the interval of its activity maximum using multiple observational parameters: sunspot number (SSN), Wolf number, the 10.7 cm solar radio flux (F10.7), the…
The dynamic activity of the Sun -- sustained by a magnetohydrodynamic dynamo mechanism working in its interior -- modulates the electromagnetic, particulate and radiative environment in space. While solar activity variations on short…
The forthcoming solar cycle (SC) 25 was beleived to be rather low when using the sunspot number (SN) as a measurement of the level of activity. The most popular prediction was made by the panel of NASA in 2019, including works based on…
The mainstream dynamo models predict that the sunspot cycle is non-stationary and stochastic. The official Solar Cycle Prediction Panel forecasts only the ongoing sunspot cycle because any forecast beyond one cycle is considered impossible.…
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 analysed the sunspot group data from Greenwich Photoheliographic Results (GPR) during 1874-1976 and Debrecen Photoheliographic Data (DPD) during 1977-2017 and studied the cycle-to-cycle variations in the values of 13-month smoothed…
Ahead-of-time forecasting of incident solar-irradiance on a panel is indicative of expected energy yield and is essential for efficient grid distribution and planning. Traditionally, these forecasts are based on meteorological physics…
We developed a solar flare prediction model using a deep neural network (DNN), named Deep Flare Net (DeFN). The model can calculate the probability of flares occurring in the following 24 h in each active region, which is used to determine…
Surface flux transport simulations for the descending phase of cycle 24 using random sources (emerging bipolar magnetic regions) with empirically determined scatter of their properties provide a prediction of the axial dipole moment during…
Regional solar power forecasting, which involves predicting the total power generation from all rooftop photovoltaic systems in a region holds significant importance for various stakeholders in the energy sector. However, the vast amount of…
In this paper, we present an application of neural networks in the renewable energy domain. We have developed a methodology for the daily prediction of global solar radiation on a horizontal surface. We use an ad-hoc time series…
Unpredictability of renewable energy sources coupled with the complexity of those methods used for various purposes in this area calls for the development of robust methods such as DL models within the renewable energy domain. Given the…
Group sunspot number (GSN) series constitute the longest instrumental astronomical database providing information on solar activity. It is a compilation of observations by many individual observers, and their inter-calibration has usually…
Total solar irradiance variations, about 0.1% between solar activity maximum and minimum, are available from accurate satellite measurements since 1978 and thus do not provide useful information on longer-term secular trends. Recently,…