9783031875748 - a gentle introduction to data, learning, and model order reduction: techniques and twinning methodologies: 174 (studies in big data, 174) de chinesta, francisco; pasquale, angelo; baillargeat, dominique; cueto, elías; champaney, victor; ghnatios, chady; ammar, amine; hascoët, nicolas; gonzález, david; alfaro, icíar; di lorenzo, daniele (7 resultados)

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book exploresthe 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 comp…rehensive 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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Taschenbuch. Condición: Neu. A Gentle Introduction to Data, Learning, and Model Order Reduction | Techniques and Twinning [.] | Francisco Chinesta (u. a.) | Taschenbuch | xvi | Englisch | 2026 | Springer | EAN 9783031875748 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[do…t]hartmann[at]springer[dot]com | Anbieter: preigu.

Idioma: Inglés
Editorial: Springer, Berlin, Arts Et Métiers Institute Of Technology, University Of Zaragoza, Springer, 2026
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book exploresthe 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 227 pp. Englisch.

A Gentle Introduction to Data, Learning, and Model Order Reduction: Techniques and Twinning Methodologies
Chinesta, Francisco; Cueto, Elías; Champaney, Victor; Ghnatios, Chady; Ammar, Amine; Hascoët, Nicolas; González, David; Alfaro, Icíar; Di Lorenzo, Daniele; Pasquale, Angelo; Baillargeat, Dominique
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A Gentle Introduction to Data, Learning, and Model Order Reduction: Techniques and Twinning Methodologies
Chinesta, Francisco; Cueto, Elías; Champaney, Victor; Ghnatios, Chady; Ammar, Amine; Hascoët, Nicolas; González, David; Alfaro, Icíar; Di Lorenzo, Daniele; Pasquale, Angelo; Baillargeat, Dominique
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A Gentle Introduction to Data, Learning, and Model Order Reduction
Chinesta, Francisco; Cueto, Elías; Champaney, Victor; Ghnatios, Chady; Ammar, Amine; Hascoët, Nicolas; González, David; Alfaro, Icíar; Di Lorenzo, Daniele; Pasquale, Angelo; Baillargeat, Dominique
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 pr…ovides 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 sectionsAround Data, Around Learning, Around Reduction, and Around Data Assimilation & Twinningthis book offers an essential resource for researchers, engineers, and students seeking to understand and apply cutting-edge simulation methodologiesSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch.