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A gentle introduction to data, learn...

Chinesta, Francisco.

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A gentle introduction to data, learning, and model order reduction = techniques and twinning methodologies /

Record Type:	Electronic resources : Monograph/item
Title/Author:	A gentle introduction to data, learning, and model order reduction/ by Francisco Chinesta ... [et al.].
Reminder of title:	techniques and twinning methodologies /
other author:	Chinesta, Francisco.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xvi, 227 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Abstract -- Extended summary -- Part 1.Around Data -- Part 2.Around Learning -- Part 3. Around Reduction -- Part 4. Around Data Assimilation & Twinning.
Contained By:	Springer Nature eBook
Subject:	Digital twins (Computer simulation) -
Online resource:	https://doi.org/10.1007/978-3-031-87572-4
ISBN:	9783031875724

A gentle introduction to data, learning, and model order reduction = techniques and twinning methodologies /
A gentle introduction to data, learning, and model order reductiontechniques and twinning methodologies /[electronic resource] :by Francisco Chinesta ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xvi, 227 p. :ill. (some col.), digital ;24 cm. - Studies in big data,v. 1742197-6511 ;. - Studies in big data ;volume 174..

Abstract -- Extended summary -- Part 1.Around Data -- Part 2.Around Learning -- Part 3. Around Reduction -- Part 4. Around Data Assimilation & Twinning.

Open access.

This open access book explores the latest advancements in simulation performance, driven by model order reduction, informed and augmented machine learning technologies and their combination into the so-called hybrid digital twins. It provides a comprehensive review of three key frameworks shaping modern engineering simulations: physics-based models, data-driven approaches, and hybrid techniques that integrate both. The book examines the limitations of traditional models, the role of data acquisition in uncovering underlying patterns, and how physics-informed and augmented learning techniques contribute to the development of digital twins. Organized into four sections-Around Data, Around Learning, Around Reduction, and Around Data Assimilation & Twinning-this book offers an essential resource for researchers, engineers, and students seeking to understand and apply cutting-edge simulation methodologies.

ISBN: 9783031875724

Standard No.: 10.1007/978-3-031-87572-4doiSubjects--Topical Terms:

3608573
Digital twins (Computer simulation)

LC Class. No.: QA76.9.C65

Dewey Class. No.: 003.3

A gentle introduction to data, learning, and model order reduction = techniques and twinning methodologies /
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505 0 $a Abstract -- Extended summary -- Part 1.Around Data -- Part 2.Around Learning -- Part 3. Around Reduction -- Part 4. Around Data Assimilation & Twinning.
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520 $a This open access book explores the latest advancements in simulation performance, driven by model order reduction, informed and augmented machine learning technologies and their combination into the so-called hybrid digital twins. It provides a comprehensive review of three key frameworks shaping modern engineering simulations: physics-based models, data-driven approaches, and hybrid techniques that integrate both. The book examines the limitations of traditional models, the role of data acquisition in uncovering underlying patterns, and how physics-informed and augmented learning techniques contribute to the development of digital twins. Organized into four sections-Around Data, Around Learning, Around Reduction, and Around Data Assimilation & Twinning-this book offers an essential resource for researchers, engineers, and students seeking to understand and apply cutting-edge simulation methodologies.
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950 $a Intelligent Technologies and Robotics (SpringerNature-42732)