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Machine Learning in Modeling and Simulation

Overview of attention for book
Cover of 'Machine Learning in Modeling and Simulation'

Table of Contents

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    Book Overview
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    Chapter 1 Machine Learning in Computer Aided Engineering
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    Chapter 2 Artificial Neural Networks
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    Chapter 3 Gaussian Processes
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    Chapter 4 Machine Learning Methods for Constructing Dynamic Models From Data
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    Chapter 5 Physics-Informed Neural Networks: Theory and Applications
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    Chapter 6 Physics-Informed Deep Neural Operator Networks
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    Chapter 7 Digital Twin for Dynamical Systems
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    Chapter 8 Reduced Order Modeling
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    Chapter 9 Regression Models for Machine Learning
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    Chapter 10 Overview on Machine Learning Assisted Topology Optimization Methodologies
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    Chapter 11 Mixed-Variable Concurrent Material, Geometry, and Process Design in Integrated Computational Materials Engineering
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    Chapter 12 Machine Learning Interatomic Potentials: Keys to First-Principles Multiscale Modeling
Attention for Chapter 10: Overview on Machine Learning Assisted Topology Optimization Methodologies
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Citations

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3 Mendeley
Summary Dimensions citations
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Chapter title
Overview on Machine Learning Assisted Topology Optimization Methodologies
Chapter number 10
Book title
Machine Learning in Modeling and Simulation
Published by
Springer, Cham, January 2023
DOI 10.1007/978-3-031-36644-4_10
Book ISBNs
978-3-03-136643-7, 978-3-03-136644-4
Authors

Chamatidis, Ilias, Stoumpos, Manos, Kazakis, George, Kallioras, Nikos Ath., Triantafyllou, Savvas, Plevris, Vagelis, Lagaros, Nikos D.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 3 100%
Readers by discipline Count As %
Engineering 3 100%

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