5G Edge Intelligence-based Refined Power Distribution Monitoring Technology and Application
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Information Systems,Software
Link
https://link.springer.com/content/pdf/10.1007/s11036-023-02212-9.pdf
Reference34 articles.
1. Ma J, Teng Z, Tang Q, Qiu W, Yang Y, Duan J (2022) Measurement error prediction of power metering equipment using improved local outlier factor and kernel support vector regression. IEEE Trans Ind Electron 69(9):9575–9585. https://doi.org/10.1109/TIE.2021.3114740
2. Gao Y, Foggo B, Yu N (2019) A physically inspired data-driven model for electricity theft detection with smart meter data. IEEE Trans Ind Inf 15(9):5076–5088. https://doi.org/10.1109/TII.2019.2898171
3. Nakutis Z, Rinaldi S, Kuzas P, Lukoius R (2020) A method for noninvasive remote monitoring of energy meter error using power consumption profile. IEEE Trans Instrum Meas 69(9):6677–6685. https://doi.org/10.1109/TIM.2020.3002402
4. Yan J, Guo Z, Yuan T, Qi S, Li N (2021) Fault prediction of intelligent electricity meter based on multi-classification machine learning model. In: 2021 IEEE international conference on artificial intelligence and computer applications (ICAICA), pp 293–297. https://doi.org/10.1109/ICAICA52286.2021.9497987
5. Wang J, Ye W, Xue T, Zhu Y, Li K (2022) Intelligent inspection enabling platform for power distribution network based on 5G wireless communication connected unmanned aerial vehicle. In: 2022 5th international conference on energy, electrical and power engineering (CEEPE), pp 574–579 (2022). https://doi.org/10.1109/CEEPE55110.2022.9783287
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