Machine Learning Techniques for Space Weather

ISBN-13: 9780128117880 / Angielski / Miękka / 2018 / 454 str.

Enrico Camporeale; Simon Wing; Jay Johnson

Spis treści

Space Weather 1. Societal and Economic Importance of Space Weather 2. Data Availability and Forecast Products for Space Weather

Machine Learning 3. Information Theory 4. Regression 5. Classification

Applications 6. Geo-effectiveness of Solar Wind Parameter: An Information Theory Approach 7. Emergence of Dynamical Complexity in the Earth's Magnetosphere 8. Applications of NARMAX in Space Weather 9. Many Hours Ahead Prediction of Geomagnetic Storms with Gaussian Processes 10. Prediction of Mev Electron Fluxes with Autoregressive Models 11. Forecast of Solar Wind Parameters Using Kalman Filter 12. Artificial Neural Networks for Determining Magnetospheric Conditions 13. Reconstruction of Plasma Electron Density from Satellite Measurements via Artifical Neural Networks 14. Classification of Magnetospheric Particle Distributions via NN 15. Automated Solar Flare Prediction 16. Coronal Holes Detection using Supervised Classification 17. CME Classification via k-means Clustering Algorithm