A Gentle Introduction to Data, Learning, and Model Order Reduction
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 mo...
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| Հիմնական հեղինակներ: | , , , , , , , , , , |
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| Ձևաչափ: | Online |
| Լեզու: | անգլերեն |
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Springer Nature
2025
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| Խորագրեր: | |
| Առցանց հասանելիություն: | ONIX_20250813T121456_9783031875724_10 |
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Չկան պիտակներ, Եղեք առաջինը, ով նշում է այս գրառումը!
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| _version_ | 1869522252082446336 |
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| author | Chinesta, Francisco Cueto, Elías Champaney, Victor Ghnatios, Chady Ammar, Amine Hascoët, Nicolas González, David Alfaro, Icíar Di Lorenzo, Daniele Pasquale, Angelo Baillargeat, Dominique |
| author_browse | Alfaro, Icíar Ammar, Amine Baillargeat, Dominique Champaney, Victor Chinesta, Francisco Cueto, Elías Di Lorenzo, Daniele Ghnatios, Chady González, David Hascoët, Nicolas Pasquale, Angelo |
| author_facet | Chinesta, Francisco Cueto, Elías Champaney, Victor Ghnatios, Chady Ammar, Amine Hascoët, Nicolas González, David Alfaro, Icíar Di Lorenzo, Daniele Pasquale, Angelo Baillargeat, Dominique |
| author_sort | Chinesta, Francisco |
| collection | Directory of Open Access Books |
| description | 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 |
| format | Online |
| id | doab-20.500.12854ir-165915 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1659152025-08-14T05:10:53Z 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 Data reduction Machine learning Model Order Reduction Digital Twins Hybrid modelling thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysis thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning 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 2025-08-14T05:10:53Z 2025-08-14T05:10:53Z 2025-08-13T10:17:31Z 2025 book ONIX_20250813T121456_9783031875724_10 https://library.oapen.org/handle/20.500.12657/105421 9783031875724 9783031875717 https://directory.doabooks.org/handle/20.500.12854/165915 eng Studies in Big Data open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/105421/1/9783031875724.pdf Springer Nature Springer Nature Switzerland 10.1007/978-3-031-87572-4 10.1007/978-3-031-87572-4 9fa3421d-f917-4153-b9ab-fc337c396b5a 85b0bcd5-dc24-44d0-a594-ea4911a410c8 38ae58dc-7456-45e1-9446-26daa3825ee5 9783031875724 9783031875717 Springer Nature Switzerland 227 Cham [...] [...] open access |
| spellingShingle | Data reduction Machine learning Model Order Reduction Digital Twins Hybrid modelling thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysis thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning Chinesta, Francisco Cueto, Elías Champaney, Victor Ghnatios, Chady Ammar, Amine Hascoët, Nicolas González, David Alfaro, Icíar Di Lorenzo, Daniele Pasquale, Angelo Baillargeat, Dominique A Gentle Introduction to Data, Learning, and Model Order Reduction |
| title | A Gentle Introduction to Data, Learning, and Model Order Reduction |
| title_full | A Gentle Introduction to Data, Learning, and Model Order Reduction |
| title_fullStr | A Gentle Introduction to Data, Learning, and Model Order Reduction |
| title_full_unstemmed | A Gentle Introduction to Data, Learning, and Model Order Reduction |
| title_short | A Gentle Introduction to Data, Learning, and Model Order Reduction |
| title_sort | gentle introduction to data learning and model order reduction |
| topic | Data reduction Machine learning Model Order Reduction Digital Twins Hybrid modelling thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysis thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning |
| topic_facet | Data reduction Machine learning Model Order Reduction Digital Twins Hybrid modelling thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::P Mathematics and Science::PB Mathematics::PBK Calculus and mathematical analysis::PBKS Numerical analysis thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning |
| url | ONIX_20250813T121456_9783031875724_10 |
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