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Computational Mechanics with Neural Networks [electronic resource] / by Genki Yagawa, Atsuya Oishi.

By: Yagawa, Genki [author.].
Contributor(s): Oishi, Atsuya [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes on Numerical Methods in Engineering and Sciences: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2021Edition: 1st ed. 2021.Description: XII, 228 p. 79 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030661113.Subject(s): Mechanics, Applied | Neural networks (Computer science)  | System theory | Machine learning | Engineering Mechanics | Mathematical Models of Cognitive Processes and Neural Networks | Complex Systems | Machine LearningAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 620.1 Online resources: Click here to access online
Contents:
Part I: Machine Learning Technologies for Computational Mechanics.-Chapter 1. Computers and Network -- Chapter 2. Feedforward Neural Networks -- Chapter 3. Deep Learning -- Chapter 4. Mutually Connected Neural Networks -- Chapter 5. Other Neural Networks.-Chapter 6. Other Algorithms and Systems -- Part II Applications: Chapter 7. Introductory Remarks. Chapter 8. Constitutive Models -- Chapter 9. Numerical Quadrature -- Chapter 10. Identifications of Analysis Parameters.
In: Springer Nature eBookSummary: This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other machine learning methods 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.
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Part I: Machine Learning Technologies for Computational Mechanics.-Chapter 1. Computers and Network -- Chapter 2. Feedforward Neural Networks -- Chapter 3. Deep Learning -- Chapter 4. Mutually Connected Neural Networks -- Chapter 5. Other Neural Networks.-Chapter 6. Other Algorithms and Systems -- Part II Applications: Chapter 7. Introductory Remarks. Chapter 8. Constitutive Models -- Chapter 9. Numerical Quadrature -- Chapter 10. Identifications of Analysis Parameters.

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other machine learning methods 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.

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