Overview
- Focuses on both computational mechanics and deep learning
- Written in an easy-to-understand manner with detailed mathematical formulas
- Include samples for practice
Part of the book series: Lecture Notes on Numerical Methods in Engineering and Sciences (LNNMES)
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About this book
This book is intended for students, engineers, and researchers interested in both computational mechanics and deep learning. It presents the mathematical and computational foundations of Deep Learning with detailed mathematical formulas in an easy-to-understand manner. It also discusses various applications of Deep Learning in Computational Mechanics, with detailed explanations of the Computational Mechanics fundamentals selected there. Sample programs are included for the reader to try out in practice. This book is therefore useful for a wide range of readers interested in computational mechanics and deep learning.
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Table of contents (10 chapters)
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Front Matter
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Fundamentals
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Front Matter
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Computational Procedures
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Front Matter
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Back Matter
Authors and Affiliations
About the authors
Genki Yagawa received his Ph.D. from University of Tokyo in 1970. He became Professor at University of Tokyo in 1984 and Director and Professor at Center for Computational Mechanics Research of Toyo University in 2004. Currently, he is an Emeritus Professor at University of Tokyo and Toyo University, Chairman of Nuclear Safety Research Association, and Member of Science Council of Japan. His awards and honors include the Order of the Sacred Treasure, Gold Rays with Neck Ribbon endowed from His Majesty the Japanese Emperor, Japan Academy Prize, International Association for Computational Mechanics Award, Asia Pacific Association Computational Mechanics Zienkiewicz Medal, Prime Minister Award, Minister of Science and Technology Award, Toray Science and Technology Medal, Honorary Doctor Endowed from Iasi Technical University, and Fellow of International Association for Computational Mechanics, Japan Society for Industrial and Applied Mathematics, Japan Society for Simulation Technology and Atomic Energy Society of Japan.
Atsuya Oishi received his Ph.D. from University of Tokyo in 1996. He became Lecturer at University of Tokushima in 1997 and has been an Associate Professor at University of Tokushima since 2006. His awards include the outstanding paper award from Japan Society for Computational Engineering and Science and JACM fellow award from Japan Association for Computational Mechanics.
Bibliographic Information
Book Title: Computational Mechanics with Deep Learning
Book Subtitle: An Introduction
Authors: Genki Yagawa, Atsuya Oishi
Series Title: Lecture Notes on Numerical Methods in Engineering and Sciences
DOI: https://doi.org/10.1007/978-3-031-11847-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-11846-3Published: 01 November 2022
Softcover ISBN: 978-3-031-11849-4Published: 02 November 2023
eBook ISBN: 978-3-031-11847-0Published: 31 October 2022
Series ISSN: 1877-7341
Series E-ISSN: 1877-735X
Edition Number: 1
Number of Pages: XIV, 402
Number of Illustrations: 40 b/w illustrations, 141 illustrations in colour
Topics: Mechanical Engineering, Computational Intelligence, Artificial Intelligence