Machine Learning In Heliophysics
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Machine Learning In Heliophysics
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Author : Thomas Berger
language : en
Publisher: Frontiers Media SA
Release Date : 2021-11-24
Machine Learning In Heliophysics written by Thomas Berger and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-24 with Science categories.
Machine Learning Techniques For Space Weather
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Author : Enrico Camporeale
language : en
Publisher: Elsevier
Release Date : 2018-05-31
Machine Learning Techniques For Space Weather written by Enrico Camporeale and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-31 with Science categories.
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
Machine Learning Techniques For Space Weather
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Author : Enrico Camporeale
language : en
Publisher:
Release Date : 2018-06
Machine Learning Techniques For Space Weather written by Enrico Camporeale and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06 with categories.
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(R) scripts that allow for replication of results in the book, also familiarizing readers with algorithms
Deep Learning For Physics Research
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Author : Martin Erdmann
language : en
Publisher: World Scientific
Release Date : 2021-06-25
Deep Learning For Physics Research written by Martin Erdmann and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Science categories.
A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning. Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.
Progress Toward Implementation Of The 2013 Decadal Survey For Solar And Space Physics
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2020-06-29
Progress Toward Implementation Of The 2013 Decadal Survey For Solar And Space Physics written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Science categories.
The 2013 report Solar and Space Physics; A Science for a Technological Society outlined a program of basic and applied research for the period 2013-2022. This publication describes the most significant scientific discoveries, technical advances, and relevant programmatic changes in solar and space physics since the publication of that decadal survey. Progress Toward Implementation of the 2013 Decadal Survey for Solar and Space Physics assesses the degree to which the programs of the National Science Foundation and the National Aeronautics and Space Administration address the strategies, goals, and priorities outlined in the 2013 decadal survey, and the progress that has been made in meeting those goals. This report additionally considers steps to enhance career opportunities in solar and space physics and recommends actions that should be undertaken to prepare for the next decadal survey.
Earth Affecting Solar Transients
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Author : Jie Zhang
language : en
Publisher: Springer
Release Date : 2018-10-27
Earth Affecting Solar Transients written by Jie Zhang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-27 with Science categories.
Earth-affecting solar transients encompass a broad range of phenomena, including major solar flares, CMEs, ICMEs, solar energetic particle events, and corotating interaction regions. In the past decade, nearly continuous observations of the Sun and the inner heliosphere with an unprecedented wide spatial coverage from a fleet of spacecraft, including STEREO Ahead/Behind, SDO, SOHO, Messenger, Venus Express, ACE and WIND, in combination with a significant advancement of global MHD numerical simulation and theoretical analysis, have greatly improved our understanding of solar transients and the prediction of their potential impact on Earth. This Topical Collection is based on the International Study of Earth-affecting Solar Transients (ISEST) project, initially launched in 2013 to bring together scientists from many countries to join efforts on studying solar transients. ISEST became one of the four research projects of the Variability of the Sun and Its Terrestrial Impact (VarSITI) program, sponsored by the Scientific Committee on Solar-Terrestrial Physics (SCOSTEP) for the period of 2014 – 2018. Originally published in the journal Solar Physics, volumes 292 (2017) and 293 (2018).
Physics Of Data Science And Machine Learning
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Author : Ijaz A. Rauf
language : en
Publisher: CRC Press
Release Date : 2021-11-28
Physics Of Data Science And Machine Learning written by Ijaz A. Rauf and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-28 with Computers categories.
Physics of Data Science and Machine Learning links fundamental concepts of physics to data science, machine learning, and artificial intelligence for physicists looking to integrate these techniques into their work. This book is written explicitly for physicists, marrying quantum and statistical mechanics with modern data mining, data science, and machine learning. It also explains how to integrate these techniques into the design of experiments, while exploring neural networks and machine learning, building on fundamental concepts of statistical and quantum mechanics. This book is a self-learning tool for physicists looking to learn how to utilize data science and machine learning in their research. It will also be of interest to computer scientists and applied mathematicians, alongside graduate students looking to understand the basic concepts and foundations of data science, machine learning, and artificial intelligence. Although specifically written for physicists, it will also help provide non-physicists with an opportunity to understand the fundamental concepts from a physics perspective to aid in the development of new and innovative machine learning and artificial intelligence tools. Key Features: Introduces the design of experiments and digital twin concepts in simple lay terms for physicists to understand, adopt, and adapt. Free from endless derivations; instead, equations are presented and it is explained strategically why it is imperative to use them and how they will help in the task at hand. Illustrations and simple explanations help readers visualize and absorb the difficult-to-understand concepts. Ijaz A. Rauf is an adjunct professor at the School of Graduate Studies, York University, Toronto, Canada. He is also an associate researcher at Ryerson University, Toronto, Canada and president of the Eminent-Tech Corporation, Bradford, ON, Canada.
Handbook On Big Data And Machine Learning In The Physical Sciences In 2 Volumes
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Author :
language : en
Publisher: World Scientific
Release Date : 2020-03-10
Handbook On Big Data And Machine Learning In The Physical Sciences In 2 Volumes written by and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-10 with Computers categories.
This compendium provides a comprehensive collection of the emergent applications of big data, machine learning, and artificial intelligence technologies to present day physical sciences ranging from materials theory and imaging to predictive synthesis and automated research. This area of research is among the most rapidly developing in the last several years in areas spanning materials science, chemistry, and condensed matter physics.Written by world renowned researchers, the compilation of two authoritative volumes provides a distinct summary of the modern advances in instrument — driven data generation and analytics, establishing the links between the big data and predictive theories, and outlining the emerging field of data and physics-driven predictive and autonomous systems.
Deep Learning And Physics
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Author : Akinori Tanaka
language : en
Publisher: Springer Nature
Release Date : 2021-03-24
Deep Learning And Physics written by Akinori Tanaka and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-24 with Science categories.
What is deep learning for those who study physics? Is it completely different from physics? Or is it similar? In recent years, machine learning, including deep learning, has begun to be used in various physics studies. Why is that? Is knowing physics useful in machine learning? Conversely, is knowing machine learning useful in physics? This book is devoted to answers of these questions. Starting with basic ideas of physics, neural networks are derived naturally. And you can learn the concepts of deep learning through the words of physics. In fact, the foundation of machine learning can be attributed to physical concepts. Hamiltonians that determine physical systems characterize various machine learning structures. Statistical physics given by Hamiltonians defines machine learning by neural networks. Furthermore, solving inverse problems in physics through machine learning and generalization essentially provides progress and even revolutions in physics. For these reasons, in recent years interdisciplinary research in machine learning and physics has been expanding dramatically. This book is written for anyone who wants to learn, understand, and apply the relationship between deep learning/machine learning and physics. All that is needed to read this book are the basic concepts in physics: energy and Hamiltonians. The concepts of statistical mechanics and the bracket notation of quantum mechanics, which are explained in columns, are used to explain deep learning frameworks. We encourage you to explore this new active field of machine learning and physics, with this book as a map of the continent to be explored.
Artificial Intelligence For Space Ai4space
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Author : Matteo Madi
language : en
Publisher: CRC Press
Release Date : 2023-12-18
Artificial Intelligence For Space Ai4space written by Matteo Madi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-18 with Science categories.
Key Features: Provides an interdisciplinary approach, with chapter contributions from expert teams working in the governmental or private space sectors, with valuable contributions from computer scientists and legal experts; Presents insights into AI implementation and how to unlock AI technologies in the field; Up to date with the latest developments and cutting-edge applications