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G. Deconinck

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Preprint Sep 2026

Hard-Constrained Probabilistic Factor Graph Neural Network for Distribution System State Estimation under Non-Gaussian Uncertainty

Robust and accurate state estimation is fundamental for the reliable operation and monitoring of active distribution networks. Conventional numerical estimators, such as weighted least squares, are computationally slower and often suffer from convergence issues in the presence of sparse measurements affected by non-Gau...

M. Azam, M. Vanin, Chris Hermans et al. · 0 citations
Sep 2026

A Neural Network-Based Model Order Reduction Methodology With Harmonic Forecasting for Parametric Nonlinear Magnetodynamic Simulations

High-fidelity parametric simulations of nonlinear magnetodynamic systems are computationally demanding, making real-time and many-query applications impractical with conventional finite element methods (FEMs). While model order reduction (MOR) techniques address this challenge, extending them to nonlinear, time-depende...

Sina Toghranegar, H. Kazmi, G. Deconinck et al. · 0 citations

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