75 citations · 203 across the 24 of their papers we have counts for
14 papers · 1 filter
SWAN-SF-V2: A Multivariate Time Series Dataset for Space Weather Data Analytics; Now with AIA and Weighted SHARP Parameters
Dustin Kempton, Griffin Goodwin, Reet Gupta +4
Since its original publication in 2020, the SWAN-SF dataset has been cited in over 300 research publications. Here we describe a comprehensive update to the original multivariate t…
A Multimodal Tiered Magnetic Polarity Inversion Features Dataset for Space Weather Forecasting
Ziba Khani, Anli Ji, Manolis K. Georgoulis +1
This article presents a publicly available, multimodal, tiered magnetic polarity inversion lines (MPILs) dataset extracted from the Solar Dynamics Observatory's (SDO) Helioseismic…
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…
Precise and Accurate Short-term Forecasting of Solar Energetic Particle Events with Multivariate Time Series Classifiers
Sumanth A. Rotti, Berkay Aydin, Petrus C. Martens
Solar energetic particle (SEP) events are one of the most crucial aspects of space weather that require continuous monitoring and forecasting using robust methods. We demonstrate a…
Short-term Classification of Strong Solar Energetic Particle Events using Multivariate Time Series Classifiers
Sumanth A. Rotti, Berkay Aydin, Petrus C. Martens
Solar energetic particle (SEP) events are one of the most crucial aspects of space weather that require continuous monitoring and forecasting. Their prediction depends on various f…
Active Region-based Flare Forecasting with Sliding Window Multivariate Time Series Forest Classifiers
Anli Ji, Berkay Aydin
Over the past few decades, many applications of physics-based simulations and data-driven techniques (including machine learning and deep learning) have emerged to analyze and pred…