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Computational mechanics with deep le...

Yagawa, Genki.

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Computational mechanics with deep learning = an introduction /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Computational mechanics with deep learning/ by Genki Yagawa, Atsuya Oishi.
Reminder of title:	an introduction /
Author:	Yagawa, Genki.
other author:	Oishi, Atsuya.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xiv, 402 p. :ill., digital ;24 cm.
[NT 15003449]:	1. Overview -- 2. Mathematical Background for Deep Learning -- 3. Computational Mechanics with Deep Learning -- 4. Numerical Quadrature with Deep Learning -- 5. Improvement of Finite Element Solutions with Deep Learning -- 6. Contact Mechanics with Deep Learning -- 7. Flow Simulation with Deep Learning -- 8. Further Applications with Deep Learning -- 9. Bases for Computer Programming -- 10. Computer Programming for a Representative Problem.
Contained By:	Springer Nature eBook
Subject:	Mechanics, Applied - Data processing. -
Online resource:	https://doi.org/10.1007/978-3-031-11847-0
ISBN:	9783031118470

Computational mechanics with deep learning = an introduction /
Yagawa, Genki.

Computational mechanics with deep learningan introduction /[electronic resource] :by Genki Yagawa, Atsuya Oishi. - Cham :Springer International Publishing :2023. - xiv, 402 p. :ill., digital ;24 cm. - Lecture notes on numerical methods in engineering and sciences,1877-735X. - Lecture notes on numerical methods in engineering and sciences..

1. Overview -- 2. Mathematical Background for Deep Learning -- 3. Computational Mechanics with Deep Learning -- 4. Numerical Quadrature with Deep Learning -- 5. Improvement of Finite Element Solutions with Deep Learning -- 6. Contact Mechanics with Deep Learning -- 7. Flow Simulation with Deep Learning -- 8. Further Applications with Deep Learning -- 9. Bases for Computer Programming -- 10. Computer Programming for a Representative Problem.

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.

ISBN: 9783031118470

Standard No.: 10.1007/978-3-031-11847-0doiSubjects--Topical Terms:

604016
Mechanics, Applied
--Data processing.

LC Class. No.: TA350

Dewey Class. No.: 620.100285631

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100 1 $a Yagawa, Genki. $3 3491266
245 1 0 $a Computational mechanics with deep learning $h [electronic resource] : $b an introduction / $c by Genki Yagawa, Atsuya Oishi.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a xiv, 402 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes on numerical methods in engineering and sciences, $x 1877-735X
505 0 $a 1. Overview -- 2. Mathematical Background for Deep Learning -- 3. Computational Mechanics with Deep Learning -- 4. Numerical Quadrature with Deep Learning -- 5. Improvement of Finite Element Solutions with Deep Learning -- 6. Contact Mechanics with Deep Learning -- 7. Flow Simulation with Deep Learning -- 8. Further Applications with Deep Learning -- 9. Bases for Computer Programming -- 10. Computer Programming for a Representative Problem.
520 $a 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.
650 0 $a Mechanics, Applied $x Data processing. $3 604016
650 0 $a Deep learning (Machine learning) $3 3538509
650 1 4 $a Engineering Mechanics. $3 3538834
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
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