Measurement Error Prediction of Power Metering Equipment Using Improved Local Outlier Factor and Kernel Support Vector Regression

The measurement error evaluation of power metering equipment (PME) is significant for the instrument design and accurate metering of electric energy, especially under extreme environmental stresses. However, actual measurement error assessment is often disturbed by the environmental noise and insuff...

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Vydané v:	IEEE transactions on industrial electronics (1982) Ročník 69; číslo 9; s. 9575 - 9585
Hlavní autori:	Ma, Jun, Teng, Zhaosheng, Tang, Qiu, Qiu, Wei, Yang, Yingying, Duan, Junfeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.09.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Background noise Companies Data analysis Degradation Error analysis Extreme environmental stresses improved kernel support vector regression (ILOF) Kernel kernel support vector regression (KSVR) Kernels Measurement measurement error assessment Measurement errors Metering Outliers (statistics) power metering equipment (PME) Reliability Stress Stresses Support vector machines Temperature measurement
ISSN:	0278-0046, 1557-9948
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