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Title:

Deep Learning in Computational Mechanics

Subtitle:
An Introductory Course
Document type:
Buch
Author(s):
Kollmannsberger, S.; D'Angella, D.; Jokeit, M.; Herrmann, L.
Editor:
Springer
Faculty:
Ingenieurfakultät Bau Geo Umwelt (BGU)
Chair:
Computational Modeling and Simulation
Abstract:
This book provides a first course on deep learning in computational mechanics. The book starts with a short introduction to machine learning’s fundamental concepts before neural networks are explained thoroughly. It then provides an overview of current topics in physics and engineering, setting the stage for the book’s main topics: physics-informed neural networks and the deep energy method. The idea of the book is to provide the basic concepts in a mathematically sound manner and yet to stay...     »
Keywords:
Deep Learning; Computational Mechanics: Neural Networks
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Bookseries title:
Studies in Computational Intelligence
Edition:
1
Publisher:
Springer
Pages:
125
Year:
2021
Year / month:
2021-08
Month:
Aug
Date of publication:
12.08.2021
Quarter:
3. Quartal
Other Issue::
0
Issue type:
Hardcover
Covered by:
Scopus; Web of Science
Price for print edition:
83,19 €
Print-ISBN:
978-3-030-76586-6
Reviewed:
ja
Language:
en
WWW:
https://www.springer.com/gp/book/9783030765866
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