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Mining PMU Data Streams to Improve Electric Power System Re..:

, In: Proceedings of the Fourth IEEE/ACM International Conference on Big Data Computing, Applications and Technologies,

Jiang, Jun ; Zhao, Xinghui ; Wallace, Scott.. - p. 95-102 , 2017

Link: https://dl.acm.org/doi/10.1145/3148055.3148082

RT 
T1 <cTitle>Proceedings of the Fourth IEEE/ACM International Conference on Big Data Computing, Applications and Technologies</cTitle>: T1 <Title>Mining PMU Data Streams to Improve Electric Power System Resilience</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3148082&Exemplar=1&LAN=DE
				
A1 Jiang, Jun
A1 Zhao, Xinghui
A1 Wallace, Scott
A1 Cotilla-Sanchez, Eduardo
A1 Bass, Robert
PB ACM
YR 2017
K1 artificial neural network (ann)
K1 cyber security
K1 data analytics
K1 machine learning
K1 phasor measurement unit (pmu)
K1 smart grid
K1 support vector machine (svm)
K1 tensorflow
K1 Security and privacy
K1 Intrusion/anomaly detection and malware mitigation
K1 Social engineering attacks
K1 Spoofing attacks
K1 Hardware
K1 Power and energy
K1 Energy distribution
K1 Smart grid
K1 Computing methodologies
K1 Machine learning
K1 Machine learning approaches
SP 95
OP 102
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3148055.3148082
DO https://dl.acm.org/doi/10.1145/3148055.3148082
SF ELIB - SuUB Bremen

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