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Machine Learning Techniques for Space Weather 1st Edition Enrico Camporeale (Editor) – eBook PDF

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Machine Learning Techniques for Space Weather – Ebook PDF

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Machine Learning Techniques for Space Weather – Ebook PDF Instant Delivery – ISBN(s): 9780128117880,0128117885

Product details:

  • ISBN-13: 978-0128117880
  • Author: Enrico Camporeale , Simon Wing , Jay Johnson 
Machine Learning Techniques for Space Weather provides a thorough and accessible presentation of machine learning techniques that can be employed by space weather professionals. Additionally, it presents an overview of real-world applications in space science to the machine learning community, offering a bridge between the fields. As this volume demonstrates, real advances in space weather can be gained using nontraditional approaches that take into account nonlinear and complex dynamics, including information theory, nonlinear auto-regression models, neural networks and clustering algorithms.

Table of contents:

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

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