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1 Ergebnisse
1
Non-intrusive Runtime Monitoring for Power System Intellige..:
, In:
2019 4th International Conference on Power and Renewable Energy (ICPRE)
,
LV, Zhining
;
HU, Ziheng
;
NING, Baifeng
... - p. 361-365 , 2019
Link:
https://doi.org/10.1109/ICPRE48497.2019.9034805
RT T1 <cTitle>2019 4th International Conference on Power and Renewable Energy (ICPRE)</cTitle>: T1 <Title>Non-intrusive Runtime Monitoring for Power System Intelligent Terminal Based on Improved Deep Belief Networks (I-DBN)</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9034805&Exemplar=1&LAN=DE A1 LV, Zhining A1 HU, Ziheng A1 NING, Baifeng A1 DING, Lifu A1 YAN, Gangfeng A1 SHI, Xiasheng YR 2019 K1 Monitoring K1 Power systems K1 Meters K1 Feature extraction K1 Classification algorithms K1 Data processing K1 Neurons K1 runtime monitoring K1 fault detection K1 cyber attack detection K1 deep belief network K1 business-level monitoring platform SP 361 OP 365 LK http://dx.doi.org/https://doi.org/10.1109/ICPRE48497.2019.9034805 DO https://doi.org/10.1109/ICPRE48497.2019.9034805 SF ELIB - SuUB Bremen
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