Review of Machine Learning Models for Solar Energetic Particle Prediction

2026-06-17 · Source: Artificial Intelligence · Field: Science & Research — Space Science & Astronomy, Artificial Intelligence & Machine Learning · Depth: Expert, quick

Summary

A comprehensive review published on 2026-06-17 examines currently available machine learning (ML) models for Solar Energetic Particle (SEP) prediction. SEP events pose significant radiation hazards to aviation, spacecraft electronics, and human space missions, while also offering crucial scientific insights into particle acceleration and transport mechanisms. This review identifies and compares the datasets, architectures, inputs, and outputs of various ML models used for SEP prediction, contrasting them with traditional physics-based simulations and empirical methods. The analysis aims to outline good practices and provide recommendations for future research in this critical area, enhancing both space weather forecasting capabilities and fundamental astrophysical understanding.

Key takeaway

For AI Scientists and Research Scientists developing space weather forecasting tools, this review highlights the evolving landscape of ML models for Solar Energetic Particle prediction. You should consider the diverse model architectures and datasets identified to inform your design choices, focusing on the outlined good practices to improve prediction accuracy and reliability. This will help safeguard critical space infrastructure and human missions from radiation hazards.

Key insights

Machine learning offers a promising new approach to predict hazardous Solar Energetic Particle events, complementing traditional methods.

Principles

• ML models enhance SEP prediction.
• Datasets, architectures, inputs vary.
• Good practices guide future research.

Method

The review systematically compares ML models for SEP prediction, analyzing their architectures, inputs, outputs, and training datasets to identify best practices.

In practice

• Evaluate diverse ML architectures.
• Utilize varied SEP event datasets.
• Apply identified good practices.

Topics

• Solar Energetic Particles
• Machine Learning Models
• Space Weather Forecasting
• Radiation Hazards
• Particle Acceleration
• Astrophysical Phenomena

Best for: AI Scientist, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.