Machine Learning Techniques for Space Weather

By: Wing, Johnson, Camporeale

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Paperback | 22 May 2018 | Edition Number 1

At a Glance

Paperback
454 Pages

Dimensions(cm)
23.5 x 19.1 x 2.31

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Machine Learning Techniques for Space Weather provides a thorough and accessible presentation of machine learning techniques to 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.

Offering practical techniques for translating the huge amount of information hidden in data into useful knowledge that allows for better prediction, Machine Learning Techniques for Space Weather is a unique and important resource for space physicists, space weather professionals, and computer scientists in related fields.

Collects many representative non-traditional approaches to space weather into a single volume
Covers in an accessible way the mathematical background that is not often explained in detail for space scientists
Includes free software in the form of simple MATLAB® scripts that would allow for replication of the results shown in the book, and familiarizing readers with the algorithms

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