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Supervised learning for fault classification using hybrid t..:

, In: 27th International Conference on Electricity Distribution (CIRED 2023),

Ranganathan, A. ; Tindemans, S. H. ; Provoost, F. - p. None , 2023

Link: https://doi.org/10.1049/icp.2023.1136

RT 
T1 <cTitle>27th International Conference on Electricity Distribution (CIRED 2023)</cTitle>: T1 <Title>Supervised learning for fault classification using hybrid training datasets</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10267441&Exemplar=1&LAN=DE
				
A1 Ranganathan, A.
A1 Tindemans, S. H.
A1 Provoost, F.
YR 2023
K1 fault diagnosis
K1 Fourier analysis
K1 learning (artificial intelligence)
K1 pattern classification
K1 power engineering computing
K1 supervised learning
K1 support vector machines
K1 accurate fault classification
K1 classification accuracy
K1 classification model
K1 customer power supply
K1 developed SVM model
K1 distribution system operator
K1 electrical faults
K1 faster network restoration times
K1 fault phases
K1 fault waveforms
K1 hybrid training datasets
K1 machine learning model
K1 real-world faults
K1 synthetically developed faults
K1 threephase stable faults
K1 two-phase
SP None
LK http://dx.doi.org/https://doi.org/10.1049/icp.2023.1136
DO https://doi.org/10.1049/icp.2023.1136
SF ELIB - SuUB Bremen

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