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Machine Learning in Modeling and Simulation

Methods and Applications

Language EnglishEnglish
Book Hardback
Book Machine Learning in Modeling and Simulation Timon Rabczuk
Libristo code: 43476026
Publishers Springer, Berlin, November 2023
Machine learning (ML)  approaches have been extensively and successfully employed in various areas,... Full description
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Machine learning (ML)  approaches have been extensively and successfully employed in various areas, like in economics, medical predictions,  face recognition, credit card fraud detection, and spam filtering. There is clearly also the potential that ML techniques developed in Engineering and the Sciences will drastically increase the possibilities of analysis and accelerate the design to analysis time.  With the use of ML techniques, coupled to conventional methods like finite element and digital twin technologies, new avenues of  modeling and simulation can be opened but the potential of these ML techniques needs to still be fully harvested, with the methods developed and enhanced. The objective of this book is to provide an overview of ML in Engineering and the Sciences presenting fundamental theoretical ingredients with a focus on the next generation of computer modeling in Engineering and the Sciences in which the exciting aspects of machine learning are incorporated. The book is of value to any researcher and practitioner interested in research or applications of ML in the areas of scientific modeling and computer aided engineering.Chapter 'Machine Learning in Computer Aided Engineering' of this book is available open access under a CC BY license via link.springer.com.

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About the book

Full name Machine Learning in Modeling and Simulation
Language English
Binding Book - Hardback
Date of issue 2023
Number of pages 430
EAN 9783031366437
Libristo code 43476026
Publishers Springer, Berlin
Weight 942
Dimensions 155 x 235
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