Publications
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Modeling Equatorial to Mid-Latitudinal Global Night Time Ionospheric Plasma Irregularities Using Machine Learning KU Leuven
Abstract This study focuses on modeling the characteristics of nighttime topside Ionospheric Plasma Irregularities (PI) on a global scale. We utilize Random Forest (RF) and a one-dimensional Convolutional Neural Network (1D-CNN) model, incorporating data from the Swarm A, B, and C satellites, space weather data from the OMNIWeb data center, as well as zonal and meridional wind model data. Our objective is to simulate monthly global PI ...
An efficient energy conserving semi-Lagrangian kinetic scheme for the Vlasov-Ampere system KU Leuven
AI-ready data in space science and solar physics: problems, mitigation and action plan KU Leuven
In the domain of space science, numerous ground-based and space-borne data of various phenomena have been accumulating rapidly, making analysis and scientific interpretation challenging. However, recent trends in the application of artificial intelligence (AI) have been shown to be promising in the extraction of information or knowledge discovery from these extensive data sets. Coincidentally, preparing these data for use as inputs to the AI ...