9783031875717 - a gentle introduction to data, learning and model order reduction: techniques and twinning methodologies: 174 di chinesta, francisco; cueto, elas; champaney, victor; ghnatios, chady; ammar, amine (14 risultati)
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Hardcover. Condizione: new. Hardcover. 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 s…haping 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 methodologies 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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A Gentle Introduction to Data, Learning, and Model Order Reduction: Techniques and Twinning Methodologies (Studies in Big Data, 174)
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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Hardcover. Condizione: new. Hardcover. 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 s…haping 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 methodologies 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Hardcover. Condizione: Brand New. 243 pages. 9.25x6.10x9.49 inches. In Stock.
Lingua: Inglese
Editore: Springer, Springer Nature Switzerland Jul 2025, 2025
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Buch. Condizione: Neu. 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.
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Hardcover. Condizione: new. Hardcover. 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 s…haping 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 methodologies 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: Springer, Springer Nature Switzerland Jul 2025, 2025
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: 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 provi…des 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 244 pp. Englisch.
A Gentle Introduction to Data, Learning, and Model Order Reduction: Techniques and Twinning Methodologies (Studies in Big Data, 174)
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 (Studies in Big Data, 174)
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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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Buch. Condizione: 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 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 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 KG, Sachsenplatz 4-6, 1201 Wien 244 pp. Englisch.
