The one-century-old theory of orthogonal genetic variance decomposition originated the field of quantitative genetics and has kept on being improved ever since. Recently, serious concerns about the ...

Deep-learning model for optimised proper orthogonal decomposition of non-linear, hyperbolic, parametric PDEs based on a pre-processing method of the full-order solutions ...

Abstract: This letter proposes a novel model order reduction (MOR) approach leveraging frequency-domain proper orthogonal decomposition (POD) for partial element equivalent circuit (PEEC) models ...

Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10915-021-01462-7. Source code ...

Abstract: We applied the proper orthogonal decomposition (POD) method to extract reduced-order models to efficiently solve nonlinear electromagnetic problems governed by Maxwell's equations with ...

ABSTRACT: In this study, we introduce a numerical method to reduce the solute transport equation into a reduced form that can replicate the behavior of the model described by the original equation.