Abstract: This paper presents a new method for parametric model order reduction based on balanced truncation. Parametric model order reduction seeks to generate low-order models from larger models ...

Abstract: Balanced truncation is a well-known technique for model-order reduction with a known uniform reduction error bound. However, its practical application to ...

Vanishing Viscosity solution predicting Graph Neural Networks and Domain Decomposable Reduced Order Models based on the Discontinuous Galerking method applied to Friedrichs' systems ...

What are Machine learning algorithms in Python? Which guide should I choose?"- This guide explains explicitly the operation of Machine Learning methods and how to implement them in Python. Whether you ...

A time-averaged error indicator with POD-hGreedy is developed to drive parametric model order reduction (pMOR) for 2D unsteady natural convection in a high-aspect ...

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Fast and accurate modelling of flood inundation has gained increasing attention in recent years. One approach gaining popularity recently is the development of emulation models using data driven ...