TY  - BOOK
AU  - Chinesta,Francisco
AU  - Cueto,Elías
AU  - Champaney,Victor
AU  - Ghnatios,Chady
AU  - Ammar,Amine
AU  - Hascoët,Nicolas
AU  - González,David
AU  - Alfaro,Icíar
AU  - Di Lorenzo,Daniele
AU  - Pasquale,Angelo
AU  - Baillargeat,Dominique
ED  - SpringerLink (Online service)
TI  - A Gentle Introduction to Data, Learning, and Model Order Reduction: Techniques and Twinning Methodologies 
T2  - Studies in Big Data,
SN  - 9783031875724
AV  - Q342 
U1  - 006.3 23
PY  - 2025///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Computational intelligence
KW  - Mathematics
KW  - Data processing
KW  - Machine learning
KW  - Computational Intelligence
KW  - Computational Science and Engineering
KW  - Machine Learning
N1  - Abstract -- Extended summary -- Part 1.Around Data -- Part 2.Around Learning -- Part 3. Around Reduction -- Part 4. Around Data Assimilation & Twinning; Open Access
N2  - 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
UR  - https://doi.org/10.1007/978-3-031-87572-4
ER  -