K-means Traceability Study of Abnormal Electricity Based on Graph Neural Network-Reference-Cited by-同舟云学术

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K-means Traceability Study of Abnormal Electricity Based on Graph Neural Network

Published:2023-12-29 Issue: Volume:50 Page:1609-1613
ISSN:
Container-title:2023 3rd International Conference on Electrical Engineering and Control Science (IC2ECS)
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Author:

Xie Lei¹,Zhang Haijing¹,Yang Linlin¹,Yang Yang¹,Wang Lianjun¹,Li Hanqi¹

Affiliation:

1. State Grid Shandong Electric Power Company Marketing Service Center (Metrology Center),Jinan,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10493201/10493208/10493697.pdf?arnumber=10493697

Reference10 articles.

1. Analysis of Electricity Consumption Data Based on Cluster Analysis;Liang;Journal of Wuhan University: Engineering Edition,2017

2. Anomaly Analysis Algorithm for Power System Electricity Consumption Based on Density Clustering Technology;Tian;Automation of Electric Power Systems,2017

3. Anomaly Detection of Power Big Data Based on Improved Fast Density Peaks Clustering Algorithm;Liu;Electric Power Information and Communication Technology,2017

4. Rapid Clustering and Anomaly Detection Techniques for Large-scale Power Consumption Data Streams;Wang;Automation of Electric Power Systems,2016

5. Some Methods for Classification and Analysis of Multivariate Observations;MacQueen,1967

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Abnormal Electricity Detection of Users Based on Improved Canopy-Kmeans and Isolation Forest Algorithms;IEEE Access;2024

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