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A method for detecting high-risk electricity theft in low-voltage distribution network stations based on density clustering of IoT sensing data

Abstract In response to the increasingly concealed and sophisticated methods of electricity theft, which are difficult to comprehensively cover and detect in a timely manner, a method for identifying high-risk electricity theft behaviors in low-voltage distribution station areas based on density-bas...

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Principais autores: Jianshu Hao, Ziyuan Yang, Ruiqiang Zhang, Juan Wang
Format: Artigo
Sprog:Inglês
Udgivet: SpringerOpen 2025-10-01
Serier:Energy Informatics
Fag:
IoT sensing data
Density clustering
Low-voltage distribution station area
High-risk electricity theft behavior
LM-BP
Feature matching
Online adgang:https://doi.org/10.1186/s42162-025-00591-9
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