5 papers
SEP-PRISM Data: A multi-source dataset for solar energetic particle forecasting
Yian Yu, Yang Chen, Lulu Zhao +3
Solar energetic particle (SEP) event forecasting often involves integrating heterogeneous observations that differ in cadence, temporal coverage, format, and historical availabilit…
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…
Realtime forecasting of solar energetic particle event and proton flux using multi-source solar observations and multi-task deep learning
Yian Yu, Yang Chen, Lulu Zhao +3
Solar energetic particle (SEP) events, defined by proton flux exceeding 10 pfu in the > 10 MeV channel, pose major risks to spacecraft operations, astronaut safety, and high-latitu…
Stable Multivariate Functional Time Series Prediction for Major Geomagnetic Indices
Yian Yu, Shasha Zou, Tuija Pulkkinen +1
High\text{--}resolution scientific data, such as geomagnetic index streams, often exhibit complex temporal dependencies that can be modeled through functional data analysis. Conven…
Solar Energetic Particle Forecasting with Multi-Task Deep Learning: SEPNET
Yian Yu, Yang Chen, Lulu Zhao +3
Solar energetic particle (SEP) events pose severe threats to spacecraft, astronaut safety, and aviation operations. Accurate SEP forecasting remains a critical challenge in space w…