Related papers: Solar activity classification based on Mg II spect…
While the space of renewable energy forecasting has received significant attention in the last decade, literature has primarily focused on machine learning models that train on only one objective at a time. A host of classification (and…
Recent studies indicate that a small number of rogue solar active regions (ARs) may have a significant impact on the end-of-cycle polar field and the long-term behavior of solar activity. The impact of individual ARs can be qualified based…
Decades of in-situ solar wind measurements have clearly established the variation of solar wind physical parameters. These variable parameters have been used to classify the solar wind magnetized plasma into different types leading to…
Precisely localising solar Active Regions (AR) from multi-spectral images is a challenging but important task in understanding solar activity and its influence on space weather. A main challenge comes from each modality capturing a…
This paper presents a machine learning-based approach for predicting solar power generation with high accuracy using a 99% AUC (Area Under the Curve) metric. The approach includes data collection, pre-processing, feature selection, model…
Solar type-II radio bursts are coherent plasma emissions arising from magnetohydrodynamic shocks produced by either coronal mass ejections (CMEs) or flares. Type-II bursts sometimes show split-band emissions in the dynamic spectrum. When…
Aims. With the Solar Optical Telescope on Hinode, we investigate the basic properties of high-degree solar oscillations observed at two levels in the solar atmosphere, in the G-band (formed in the photosphere) and in the Ca II H line…
With the rapid development of telescopes, both temporal cadence and the spatial resolution of observations are increasing. This in turn generates vast amount of data, which can be efficiently searched only with automated detections in order…
We present a novel approach to perform ground-based estimation and prediction of the surface solar irradiance with the view to predicting photovoltaic energy production. We propose the use of mini-batch k-means clustering to extract…
We analyze the effect of solar features on the variability of the solar irradiance in three different spectral ranges. Our study is based on two solar-cycles' worth of full-disk photometric images from the San Fernando Observatory, obtained…
The solar interior is filled with turbulent thermal convection, which plays a key role in the energy and momentum transport and the generation of the magnetic field. The turbulent flows in the solar interior cannot be optically detected due…
Solar flare forecasting can be realized by means of the analysis of magnetic data through artificial intelligence techniques. The aim is to predict whether a magnetic active region (AR) will originate solar flares above a certain class…
Context. Solar flux atlases observe the spatially integrated light from the Sun, treating it as a star. They are fundamental tools for gaining insight into the composition of the Sun and other stars, and are utilized as reference material…
Solar activity is an important driver of long-term climate trends and must be accounted for in climate models. Unfortunately, direct measurements of this quantity over long periods do not exist. The only observation related to solar…
In this paper, we analyze the influence of characteristic solar activity parameters as well as the competition effects in solar activity and atmospheric pressure on the records of cosmic radiation based on HiSPARC (The High School Project…
Solar activity It is vital to accurately predict solar activity, in order to decrease the plausible damage of electronic equipment in the event of a large high-intensity solar eruption. Recently, we have proposed BELFIS (Brain Emotional…
The Sun's chromosphere is a critical region to understand when considering energy and mass deposition into the transition region and corona, but many of the smaller, faster events which transport a portion of this mass and energy are still…
Searches for small exoplanets around solar-type stars are limited by stellar physical variability. While chromospheric variability is well studied, observing, modeling. and understanding the much smaller fluctuations in photospheric…
Machine learning (ML) is becoming a critical tool for interrogation of large complex data. Labeling, defined as the process of adding meaningful annotations, is a crucial step of supervised ML. However, labeling datasets is time consuming.…
The solar analogs of M67 let us glimpse the probable behavior of the Sun on time scales surpassing the duration of human civilization. M67 can serve as a solar proxy because its stars share a similar age and composition with the Sun.…