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1
Research on fault prediction and diagnosis of power equipme..:
, In:
2022 Power System and Green Energy Conference (PSGEC)
,
Liangzhi, Yin
;
Ying, Li
;
Zhuo, Zhao
... - p. 1195-1199 , 2022
Link:
https://doi.org/10.1109/PSGEC54663.2022.9881104
RT T1 <cTitle>2022 Power System and Green Energy Conference (PSGEC)</cTitle>: T1 <Title>Research on fault prediction and diagnosis of power equipment based on big data</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9881104&Exemplar=1&LAN=DE A1 Liangzhi, Yin A1 Ying, Li A1 Zhuo, Zhao A1 Jiafeng, Wang A1 Nuodi, Wang A1 Xuan, Wang A1 Jinglin, Guan YR 2022 K1 Soft sensors K1 Big Data K1 Prediction algorithms K1 Market research K1 Smart grids K1 Data mining K1 Electric power big data K1 fault diagnosis K1 fault prediction algorithm SP 1195 OP 1199 LK http://dx.doi.org/https://doi.org/10.1109/PSGEC54663.2022.9881104 DO https://doi.org/10.1109/PSGEC54663.2022.9881104 SF ELIB - SuUB Bremen
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