Publikationer av Federica Bragone
Refereegranskade
Artiklar
[1]
F. Bragone et al., "Physics-informed neural networks for modelling power transformer’s dynamic thermal behaviour," Electric power systems research, vol. 211, s. 108447-108447, 2022.
Konferensbidrag
[2]
T. Laneryd et al., "Physics Informed Neural Networks for Power Transformer Dynamic Thermal Modelling," i IFAC Papersonline, 2022, s. 49-54.
[3]
F. Bragone et al., "Physics-Informed Neural Networks for Modeling Cellulose Degradation in Power Transformers," i 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 2022.
[4]
K. Oueslati et al., "Physics-Informed Neural Networks for modelling insulation paper degradation in Power Transformers," i 2022 IEEE International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM), 2022.
[5]
O. Welin Odeback et al., "Physics-Informed Neural Networks for prediction of transformer's temperature distribution," i 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA, 2022, s. 1579-1586.
[6]
O. Welin Odeback et al., "Physics-Informed Neural Networks for prediction of transformer’s temperature distribution," i 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 2022.
[7]
D. Bogatov Wilkman et al., "Self-Supervised Transformer Networks for Error Classification of Tightening Traces," i 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 2022.
Icke refereegranskade
Avhandlingar
[8]
F. Bragone, "Physics-Informed Neural Networks and Machine Learning Algorithms for Sustainability Advancements in Power Systems Components," Licentiatavhandling Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2023:69, 2023.
Övriga
[9]
F. Bragone et al., "Unsupervised Learning Analysis of Flow-Induced Birefringence in Nanocellulose: Differentiating Materials and Concentrations," (Manuskript).
Senaste synkning med DiVA:
2024-05-05 01:03:40