Overview
- Discusses neural networks and the related methods in computational mechanics
- Presents the bases on computers and networks
- Highlights machine learning methods
Part of the book series: Lecture Notes on Numerical Methods in Engineering and Sciences (LNNMES)
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Table of contents (16 chapters)
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Front Matter
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Preliminaries: Machine Learning Technologies for Computational Mechanics
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Front Matter
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Applications
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Front Matter
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Back Matter
Keywords
About this book
This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems of computational mechanics. The final chapter gives perspectives to the applications of the deep learning to computational mechanics.
Authors and Affiliations
Bibliographic Information
Book Title: Computational Mechanics with Neural Networks
Authors: Genki Yagawa, Atsuya Oishi
Series Title: Lecture Notes on Numerical Methods in Engineering and Sciences
DOI: https://doi.org/10.1007/978-3-030-66111-3
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 2021
Hardcover ISBN: 978-3-030-66110-6Published: 27 February 2021
Softcover ISBN: 978-3-030-66113-7Published: 27 February 2022
eBook ISBN: 978-3-030-66111-3Published: 26 February 2021
Series ISSN: 1877-7341
Series E-ISSN: 1877-735X
Edition Number: 1
Number of Pages: XII, 228
Number of Illustrations: 79 b/w illustrations
Topics: Mechanical Engineering, Mathematical Models of Cognitive Processes and Neural Networks, Complex Systems, Machine Learning