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Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
Open Access
LOF-RF-based anomaly data detection method for power cables
Yuyang Jiao
Yuyang Jiao
State Grid Beijing Electric Power Company Cable Branch
Beijing, China
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Jiao, Yuyang
,
Qing Liu
Qing Liu
State Grid Beijing Electric Power Company Cable Branch
Beijing, China
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Liu, Qing
,
Guang Li
Guang Li
State Grid Beijing Electric Power Company Cable Branch
Beijing, China
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Li, Guang
,
Yiduo Xiong
Yiduo Xiong
State Grid Beijing Electric Power Company Cable Branch
Beijing, China
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Xiong, Yiduo
,
Tian Guo
Tian Guo
State Grid Beijing Electric Power Company Cable Branch
Beijing, China
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Guo, Tian
,
Yi Zhou
Yi Zhou
State Grid Beijing Electric Power Company Cable Branch
Beijing, China
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Zhou, Yi
and
Tingting Wang
Tingting Wang
School of Control and Computer Engineering, North China Electric Power University
Beijing, China
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Wang, Tingting
Nov 22, 2024
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
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Published Online:
Nov 22, 2024
Received:
Jul 26, 2024
Accepted:
Oct 24, 2024
DOI:
https://doi.org/10.2478/amns-2024-3425
Keywords
<kwd>Cable anomalies</kwd>
,
<kwd>Local outliers</kwd>
,
<kwd>Random forest</kwd>
,
<kwd>Cable data</kwd>
© 2024 Yuyang Jiao et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
