A Gentle Introduction to Data Learning and Model Order Reduction (eng)

Chinesta, Francisco

ISBN 10: 3031875710 / ISBN 13: 9783031875717

Edité par Springer, 2025

A propos de cet article

N° de réf. du vendeur CAY1J0BCXG

Détails bibliographiques

• Titre: A Gentle Introduction to Data Learning and Model Order Reduction (eng)
• Éditeur: Springer
• Date de parution: 2025
• Langue: anglais
• ISBN à 10 chiffres: 3031875710
• ISBN à 13 chiffres: 9783031875717
• Reliure: Couverture rigide
• État de l'article: new
• Poids: 0,56 kilogramme

A propos de ce titre

Synopsis

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.

À propos de l'auteur

Francisco Chinesta - Professor of Computational Physics at Arts et Métiers Institute of Technology, Paris and programme director at CNRS@CREATE, Singapore. His research focuses on computational physics, model order reduction, and hybrid artificial intelligence.

Elias Cueto - Professor of Continuum Mechanics at Universidad de Zaragoza. His research covers model order reduction, artificial intelligence and computational mechanics.

Victor Champaney - Researcher at Arts et Métiers Institute of Technology, Paris. His work specializes in model order reduction, hybrid modeling and frugal AI techniques.

Chady Ghnatios - Professor of Mechanical Engineering at University of North Florida, USA. His research focuses on model order reduction, advanced simulation, machine learning and hybrid modeling.

Amine Ammar - Professor of Computational Mechanics at Arts et Métiers Institute of Technology, Angers. His expertise lies in kinetic theory models, model reduction, and computational material forming.

Nicolas Hascoët - Associate Professor at Arts et Métiers Institute of Technology, Paris. His research focuses on machine learning and data science for industrial applications.

David Gonzalez - Professor of Continuum Mechanics at Universidad de Zaragoza. His research interests include model reduction, real-time computational simulations, and physics-informed AI.

Icíar Alfaro - Associate Professor at Universidad de Zaragoza. She specializes in numerical methods, solid mechanics, and physics-informed neural networks.

Daniele Di Lorenzo - Researcher at Arts et Métiers Institute of Technology, Paris. His research focuses on inverse analysis, hybrid modeling, and digital twins for structural health monitoring.

Angelo Pasquale - Researcher in Computational Mechanics at Arts et Métiers Institute of Technology, Paris. He specializes in AI-enhanced simulations, model order reduction and multiscale modeling.

Dominique Baillargeat - Professor at the University of Limoges and Director of CNRS@CREATE at Singapore. His research focuses on high-frequency electronics, nanotechnologies, and advanced modeling and simulation techniques using Hybrid-AI.