Related papers: Nonlinear Prediction of Solar Cycle 24
The ability to predict the future behavior of solar activity has become of extreme importance due to its effect on the near Earth environment. Predictions of both the amplitude and timing of the next solar cycle will assist in estimating…
The dynamic activity of the Sun, governed by its cycle of sunspots -- strongly magnetized regions that are observed on its surface -- modulate our solar system space environment creating space weather. Severe space weather leads to…
The Sun's activity cycle governs the radiation, particle and magnetic flux in the heliosphere creating hazardous space weather. Decadal-scale variations define space climate and force the Earth's atmosphere. However, predicting the solar…
Sunspot number (SSN) is an important - albeit nuanced - parameter that can be used as an indirect measure of solar activity. Predictions of upcoming active intervals, including the peak and timing of solar maximum can have important…
We apply a complex network approach to analyse the time series of five solar parameters, and propose an strategy to predict the number of sunspots for the next solar maximum, and when will this maximum will occur. The approach is based on…
Solar cycles are studied with the Version 2 monthly smoothed international sunspot number, the variations of which are found to be well represented by the modified logistic differential equation with four parameters: maximum cumulative…
Solar variability occurs over a broad range of spatial and temporal scales, from the Sun's brightening over its lifetime to the fluctuations commonly associated with magnetic activity over minutes to years. The latter activity includes most…
A review of solar cycle prediction methods and their performance is given, including forecasts for cycle 24 and focusing on aspects of the solar cycle prediction problem that have a bearing on dynamo theory. The scope of the review is…
We present a hybrid forecasting strategy that combines numerical modeling, statistical forecasting, and machine learning methods to predict enhanced bursts of solar activity. These bursts, referred to here as space weather seasons, occur on…
Sunspot numbers form a comprehensive, long-duration proxy of solar activity and have been used numerous times to empirically investigate the properties of the solar cycle. A number of correlations have been discovered over the 24 cycles for…
Solar cycle activity forecasting, mainly its magnitude and timing, is an essential issue for numerous scientific and technological applications: in fact, during an active solar period, many strong eruptions occur on the Sun with increasing…
Forecasting the solar cycle amplitude is important for a better understanding of the solar dynamo as well as for many space weather applications. We demonstrated a steady relationship between the maximal growth rate of sunspot activity in…
With recent advances in the field of machine learning, the use of deep neural networks for time series forecasting has become more prevalent. The quasi-periodic nature of the solar cycle makes it a good candidate for applying time series…
Reliable prediction of the solar cycle is a formidable challenge, yet it is increasingly vital in our technology-dependent society as solar activity drives space weather. Various methods, including precursors, nonlinear curve fitting and…
The solar activity in the current, that is, the 24-th, sunspot cycle is analyzed. Cyclic variations in the sunspot number (SSN) and radiation fluxes in various spectral ranges have been estimated in comparison with the general level of the…
A Bayesian method for forecasting solar cycles is presented. The approach combines a Fokker--Planck description of short--timescale (daily) fluctuations in sunspot number (\citeauthor{NobleEtAl2011}, 2011, \apj{} \textbf{732}, 5) with…
The use of the spotless days to predict the future solar activity is here revised based on the new version of the sunspot number index with a 24-month filter. Data from Solar Cycle (SC) 10 are considered because from this solar cycle the…
The prediction of solar activity is important for advanced technologies and space activities. The peak sunspot number (SSN), which can represent the solar activity, has declined continuously in the past four solar cycles (21$-$24), and 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…
Using neural networks as a prediction method, we attempt to demonstrate that forecasting of the Sun's sunspot time series can be extended to the spatial-temporal case. We employ this machine learning methodology to forecast not only in time…