Progress in solar cycle predictions: Sunspot cycles 24–25 in perspective: Invited review
D Nandy - Solar Physics, 2021 - Springer
The dynamic activity of the Sun—sustained by a magnetohydrodynamic dynamo mechanism
working in its interior—modulates the electromagnetic, particulate, and radiative …
working in its interior—modulates the electromagnetic, particulate, and radiative …
Machine learning in solar physics
A Asensio Ramos, MCM Cheung, I Chifu… - Living Reviews in Solar …, 2023 - Springer
The application of machine learning in solar physics has the potential to greatly enhance our
understanding of the complex processes that take place in the atmosphere of the Sun. By …
understanding of the complex processes that take place in the atmosphere of the Sun. By …
Forecasting sunspot time series using deep learning methods
Abstract To predict Solar Cycle 25, we used the values of sunspot number (SSN), which
have been measured regularly from 1749 to the present. In this study, we converted the SSN …
have been measured regularly from 1749 to the present. In this study, we converted the SSN …
Prediction of solar cycle 25 using deep learning based long short-term memory forecasting technique
In the current work we have used the deep learning based long short-term memory model to
predict the strength and peak time of solar cycle 25 by employing the monthly smoothed …
predict the strength and peak time of solar cycle 25 by employing the monthly smoothed …
EMD and LSTM hybrid deep learning model for predicting sunspot number time series with a cyclic pattern
T Lee - Solar Physics, 2020 - Springer
The prediction of a time series such as climate indices and the sunspot number (SSN) with
long-term oscillatory behaviors has been a challenging task due to the complex combination …
long-term oscillatory behaviors has been a challenging task due to the complex combination …
A neural network‐based ionospheric model over Africa from Constellation Observing System for Meteorology, Ionosphere, and Climate and Ground Global Positioning …
The first regional total electron content (TEC) model over the entire African region (known as
AfriTEC model) using empirical observations is developed and presented. Artificial neural …
AfriTEC model) using empirical observations is developed and presented. Artificial neural …
Forecasting of sunspot time series using a hybridization of ARIMA, ETS and SVM methods
Solar activity directly influences the heliospheric environment and lives on the Earth.
Sunspot number (SN) is one of the most crucial and commonly predicted solar activity …
Sunspot number (SN) is one of the most crucial and commonly predicted solar activity …
Comparison of different predictive models and their effectiveness in sunspot number prediction
SSR Moustafa, SS Khodairy - Physica Scripta, 2023 - iopscience.iop.org
Human activities and health are significantly influenced by solar activity. The sunspot
number is one of the most commonly used measures of solar activity. The solar cycle's quasi …
number is one of the most commonly used measures of solar activity. The solar cycle's quasi …
Forward‐Looking Study of Solar Maximum Impact in 2025: Effects of Satellite Navigation Failure on Aviation Network Operation in the Greater Bay Area, China
D Xue, J Yang, Z Liu, W Cong - Space Weather, 2023 - Wiley Online Library
Satellite navigation based on the Global Navigation Satellite System can provide aircraft
with more precise guidance and increase flight efficiency. However, severe space weather …
with more precise guidance and increase flight efficiency. However, severe space weather …
Prediction of amplitude and timing of solar cycle 25
P Chowdhury, R Jain, PC Ray, D Burud, A Chakrabarti - Solar Physics, 2021 - Springer
We study the geomagnetic activity Ap-index in relation to sunspot number and area for the
interval covering Solar Cycles 17 to 24 (1932–2019), in view of the availability of data for the …
interval covering Solar Cycles 17 to 24 (1932–2019), in view of the availability of data for the …