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Rústica. Condición: New. The field of scientific artificial intelligence is fascinating. The possibility that artificial intelligence can make predictionswhether using experimental or synthetic data, or relying solely on the differential equations that govern the phe-nomena under studyis, quite simply, fascinating. The challenge is for this artificial intelligence to be truly predictive in an engineering sense: that the pre-dictions it makes can be verified and validated, so that industry can ultimately place its trust in the benefits this new discipline can bring.It is the task of engineers, physicists, and mathematicians to turn this family of techniques into the tool that industry needs right now. The responsibility lies with us, and it begins with training a new generation of researchers in the field who will, no doubt, bring this to a successful conclusion.…

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Hardcover. Condición: Brand New. 243 pages. 9.25x6.10x9.49 inches. In Stock.

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Condición: New. pp. 108 2016th edition NO-PA16APR2015-KAP.

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Paperback. Condición: Brand New. 108 pages. 9.25x6.25x0.25 inches. In Stock.

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 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.…

Hardcover. Condición: Brand New. 243 pages. 9.25x6.10x9.49 inches. In Stock.

Rústica. Condición: NUEVO. 312 pages/páginas.

Buch. 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 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.…

Condición: New. Print on Demand pp. 108.

Condición: New. PRINT ON DEMAND pp. 108.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. First PGD book intended as a manual in the basics of the methodOnly available reference that includes Matlab code to ease the processCovers some of the most popular aspects of the technique, particularly real-time simulation.…

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 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch.…