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Convolutional Adversarial Neural Network (CANN) for Fault D..:

, In: 2019 International Conference on Information and Communications Technology (ICOIACT),

Chan, S. ; Oktavianti, I. ; Puspita, V.. - p. 596-601 , 2019

Link: https://doi.org/10.1109/ICOIACT46704.2019.8938444

RT 
T1 <cTitle>2019 International Conference on Information and Communications Technology (ICOIACT)</cTitle>: T1 <Title>Convolutional Adversarial Neural Network (CANN) for Fault Diagnosis within a Power System : Addressing the Challenge of Event Correlation for Diagnosis by Power Disturbance Monitoring Equipment in a Smart Grid</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-8938444&Exemplar=1&LAN=DE
				
A1 Chan, S.
A1 Oktavianti, I.
A1 Puspita, V.
A1 Nopphawan, P.
YR 2019
K1 Generative adversarial networks
K1 Neural networks
K1 Generators
K1 Power system stability
K1 Training
K1 Fault diagnosis
K1 Monitoring
K1 Fault diagnostics
K1 power system network
K1 generative adversarial network
K1 convolutional neural network
K1 convolutional adversarial neural network
K1 event correlation
K1 disturbance monitoring
K1 grid stability/resiliency monitoring systems
SP 596
OP 601
LK http://dx.doi.org/https://doi.org/10.1109/ICOIACT46704.2019.8938444
DO https://doi.org/10.1109/ICOIACT46704.2019.8938444
SF ELIB - SuUB Bremen

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