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Model Reduction in EngineeringDavid Ryckelynck; Fabien Casenave; Nissrine Akkari978-3-031-52764-72024 Edition 1- Shows how manifold learning uses model order reduction and deep learning for training models in continuum mechanics
- Discusses high dimensional input variables in mechanical models, in particular for image-based digital twining
- Proposes practical techniques such as data augmentation or hyper-reduction in order to reduce high dimensional models
- This book is open access, which means that you have free and unlimited access
Open Access