國立虎尾科技大學 |

Deep learning in computational mechanics = an introductory course /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Deep learning in computational mechanics/ by Leon Herrmann ... [et al.].
其他題名:	an introductory course /
其他作者:	Herrmann, Leon.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xxvi, 475 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Machine learning. -
電子資源:	https://doi.org/10.1007/978-3-031-89529-6
ISBN:	9783031895296

Deep learning in computational mechanics = an introductory course /
Deep learning in computational mechanicsan introductory course /[electronic resource] :by Leon Herrmann ... [et al.]. - Second edition. - Cham :Springer Nature Switzerland :2025. - xxvi, 475 p. :ill., digital ;24 cm.

Computational Mechanics Meets Arti?cial Intelligence -- Neural Networks -- Machine Learning in Computational Mechanics -- Methodological Overview of Deep Learning in Computational Mechanics -- Index.

This book provides a first course without requiring prerequisite knowledge. Fundamental concepts of machine learning are introduced before explaining neural networks. With this knowledge, prominent topics in deep learning for simulation are explored. These include surrogate modeling, physics-informed neural networks, generative artificial intelligence, Hamiltonian/Lagrangian neural networks, input convex neural networks, and more general machine learning techniques. The idea of the book is to provide basic concepts as simple as possible but in a mathematically sound manner. Starting point are one-dimensional examples including elasticity, plasticity, heat evolution, or wave propagation. The concepts are then expanded to state-of-the-art applications in material modeling, generative artificial intelligence, topology optimization, defect detection, and inverse problems.

ISBN: 9783031895296

Standard No.: 10.1007/978-3-031-89529-6doiSubjects--Topical Terms:

561253
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Deep learning in computational mechanics = an introductory course /
LDR:02117nam a2200337 a 4500 001 1172046
003 DE-He213
005 20251124120643.0
006 m d
007 cr nn 008maaau
008 260512s2025 sz s 0 eng d
020 $a 9783031895296 $q (electronic bk.)
020 $a 9783031895289 $q (paper)
024 7 $a 10.1007/978-3-031-89529-6 $2 doi
035 $a 978-3-031-89529-6
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .D311 2025
245 0 0 $a Deep learning in computational mechanics $h [electronic resource] : $b an introductory course / $c by Leon Herrmann ... [et al.].
250 $a Second edition.
260 $a Cham : $c 2025. $b Springer Nature Switzerland : $b Imprint: Springer,
300 $a xxvi, 475 p. : $b ill., digital ; $c 24 cm.
505 0 $a Computational Mechanics Meets Arti?cial Intelligence -- Neural Networks -- Machine Learning in Computational Mechanics -- Methodological Overview of Deep Learning in Computational Mechanics -- Index.
520 $a This book provides a first course without requiring prerequisite knowledge. Fundamental concepts of machine learning are introduced before explaining neural networks. With this knowledge, prominent topics in deep learning for simulation are explored. These include surrogate modeling, physics-informed neural networks, generative artificial intelligence, Hamiltonian/Lagrangian neural networks, input convex neural networks, and more general machine learning techniques. The idea of the book is to provide basic concepts as simple as possible but in a mathematically sound manner. Starting point are one-dimensional examples including elasticity, plasticity, heat evolution, or wave propagation. The concepts are then expanded to state-of-the-art applications in material modeling, generative artificial intelligence, topology optimization, defect detection, and inverse problems.
650 0 $a Machine learning. $3 561253
650 0 $a Neural networks (Computer science) $3 528588
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Machine Learning. $3 1137723
650 2 4 $a Engineering Thermodynamics, Heat and Mass Transfer. $3 769147
700 1 $a Herrmann, Leon. $e author. $3 1356833
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-89529-6
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)