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Machine Learning Techniques for Space Weather true
By:Enrico Camporeale,Simon Wing,Jay Johnson
Published on 2018-05-31 by Elsevier

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. Offering practical techniques for translating the huge amount of information hidden in data into useful knowledge that allows for better prediction, this book 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 allow for replication of results in the book, also familiarizing readers with algorithms

This Book was ranked at 16 by Google Books for keyword Machine Learning.

Book ID of Machine Learning Techniques for Space Weather's Books is zaRBDwAAQBAJ, Book which was written byEnrico Camporeale,Simon Wing,Jay Johnsonhave ETAG "N7QLvUfcwMg"

Book which was published by Elsevier since 2018-05-31 have ISBNs, ISBN 13 Code is 9780128117897 and ISBN 10 Code is 0128117893

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Book which have "454 Pages" is Printed at BOOK under CategoryScience

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