Computational Mechanics with Neural Networks

Computational Mechanics with Neural Networks

Author: Genki Yagawa

Publisher: Springer

ISBN: 3030661105

Page: 228

Download 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.

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.



More Books:

Computational Mechanics with Neural Networks
Language: en
Pages: 228
Authors: Genki Yagawa, Atsuya Oishi
Categories: Technology & Engineering
Type: BOOK - Published: 2021-03-26 - Publisher: Springer

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
Computational Mechanics with Neural Networks
Language: en
Pages:
Authors: Genki Yagawa
Categories: Technology & Engineering
Type: BOOK - Published: - Publisher: Springer Nature

Books about Computational Mechanics with Neural Networks
Deep Learning in Computational Mechanics
Language: en
Pages:
Authors: Stefan Kollmannsberger
Categories: Technology & Engineering
Type: BOOK - Published: - Publisher: Springer Nature

Books about Deep Learning in Computational Mechanics
Deep Learning in Computational Mechanics
Language: en
Pages: 104
Authors: Stefan Kollmannsberger, Davide D'Angella, Moritz Jokeit, Leon Herrmann
Categories: Technology & Engineering
Type: BOOK - Published: 2021-09-13 - Publisher: Springer

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:
Machine Learning, Low-Rank Approximations and Reduced Order Modeling in Computational Mechanics
Language: en
Pages: 254
Authors: Felix Fritzen, David Ryckelynck
Categories: Technology & Engineering
Type: BOOK - Published: 2019-09-18 - Publisher: MDPI

The use of machine learning in mechanics is booming. Algorithms inspired by developments in the field of artificial intelligence today cover increasingly varied fields of application. This book illustrates recent results on coupling machine learning with computational mechanics, particularly for the construction of surrogate models or reduced order models. The