9783030765866 - deep learning in computational mechanics: an introductory course (studies in computational intelligence, band 977) von kollmannsberger, stefan; d'angella, davide; jokeit, moritz; herrmann, leon (2 Ergebnisse)
Deep Learning in Computational Mechanics: An Introductory Course (Studies in Computational Intelligence, 977) 1st ed. 2021 Edition
Kollmannsberger, Stefan; D'Angella, Davide; Jokeit, Moritz; Herrmann, Leon
Sprache: Englisch
Verlag: Springer, 2021
Serie: Buch 481 von 538 - Studies in Computational Intelligence
- Hardcover
Anbieter: Majestic Books, Hounslow, Vereinigtes KönigreichMajestic Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 4 SternenZustand: Neu
EUR 127,42
EUR 7,59 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 1 verfügbar
Zustand: New.
Sprache: Englisch
Verlag: Springer, Berlin, Springer, 2021
Serie: Buch 481 von 538 - Studies in Computational Intelligence
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 95,26
EUR 61,71 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 topi…cs 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 as simple as possible. To achieve this goal, mostly one-dimensional examples are investigated, such as approximating functions by neural networks or the simulation of the temperature's evolution in a one-dimensional bar.Each chapter contains examples and exercises which are either solved analytically or in PyTorch, an open-source machine learning framework for python.
