6 citations · 20 across the 10 of their papers we have counts for
10 papers
Review of Machine Learning Models for Solar Energetic Particle Prediction
Spiridon Kasapis, Pouya Hosseinzadeh, Kathryn Whitman +73
Solar energetic particle (SEP) events have attracted increasing attention due to their significant radiation hazards for aviation, spacecraft electronics, and human missions beyond…
Using ML-based Regression Techniques to Mitigate GOES Energetic Proton Flux Data Contamination and Magnetospheric Effects
Aatiya Ali, Viacheslav Sadykov
Positioned at geostationary orbit (GEO) ~36,000 km above Earth, NOAA's GOES series has recorded real-time energetic proton flux measurements crucial for space weather monitoring fo…
Comparative Analysis of 10 - 50 MeV Solar Proton Events at Lagrange Point 1 and the Geostationary Orbit
Aatiya Ali, Viacheslav Sadykov
Solar proton events (SPEs) pose radiation hazards, disrupt technology, and impact operations on Earth and in space, making continuous monitoring essential. We compare 10-50 MeV pro…
Operational and Exploration Requirements and Research Capabilities for SEP Environment Monitoring and Forecasting
Viacheslav Sadykov, Petrus Martens, Dustin Kempton +15
Mitigating risks posed by solar energetic particles (SEPs) to operations and exploration in space and Earth's atmosphere motivates the development of advanced, synergistic approach…
Time Series of Magnetic Field Parameters of Merged MDI and HMI Space-Weather Active Region Patches as Potential Tool for Solar Flare Forecasting
Paul A. Kosovich, Alexander G. Kosovichev, Viacheslav M. Sadykov +8
Solar flare prediction studies have been recently conducted with the use of Space-Weather MDI (Michelson Doppler Imager onboard Solar and Heliospheric Observatory) Active Region Pa…
Statistical Study of the Correlation between Solar Energetic Particles and Properties of Active Regions
Russell D. Marroquin, Viacheslav Sadykov, Alexander Kosovichev +9
The flux of energetic particles originating from the Sun fluctuates during the solar cycles. It depends on the number and properties of Active Regions (ARs) present in a single day…
The Random Hivemind: An Ensemble Deep Learner Application to Solar Energetic Particle Prediction Problem
Patrick M. O'Keefe, Viacheslav Sadykov, Alexander Kosovichev +8
The application of machine learning and deep learning, including the wide use of non-ensemble, conventional neural networks (CoNN), for predicting various phenomena has become very…
Predicting Solar Proton Events of Solar Cycles 22-24 using GOES Proton & soft X-Ray flux features
Aatiya Ali, Viacheslav Sadykov, Alexander Kosovichev +9
Solar Energetic Particle (SEP) events and their major subclass, Solar Proton Events (SPEs), can have unfavorable consequences on numerous aspects of life and technology, making the…
A spectroscopic survey of infrared 1-4μm spectra in regions of prominent solar coronal emission lines of Fe XIII, Si X, and Si IX
Aatiya Ali, Alin Paraschiv, Kevin Reardon +1
The infrared solar spectrum contains a wealth of physical data about the Sun and is being explored using modern detectors and technology with new ground-based solar telescopes. One…
Prediction of Solar Proton Events with Machine Learning: Comparison with Operational Forecasts and "All-Clear" Perspectives
Viacheslav Sadykov, Alexander Kosovichev, Irina Kitiashvili +7
Solar Energetic Particle events (SEPs) are among the most dangerous transient phenomena of solar activity. As hazardous radiation, SEPs may affect the health of astronauts in outer…