兵工自动化2025，Vol.44Issue(1)：38-42,5.DOI:10.7690/bgzdh.2025.01.008
基于神经网络算法的反间歇性窃电行为监测方法
Anti-intermittent Electricity Stealing Monitoring Method Based on Neural Network Algorithm
摘要
Abstract
In order to solve the problems of low average accuracy of power consumption data identification and poor accuracy of anti-intermittent electricity stealing behavior monitoring,an anti-intermittent electricity stealing behavior monitoring method based on neural network algorithm is proposed.Constructing a basic electricity-stealing analysis model,using a median filter to eliminate acquired useless data,completing the acquisition and preprocessing of power consumption data,applying a neural network back propagation algorithm to optimize an electricity-stealing behavior monitoring neural network model,setting an intermittent electricity-stealing behavior identification function,and realizing the monitoring of the intermittent electricity-stealing behavior;The experimental link was constructed,and the application effect of this method was analyzed by F1 value and average accuracy.The experimental results show that this method improves the ability of data analysis,and further improves the accuracy of anti-intermittent electricity theft monitoring.关键词
神经网络算法/反间歇性窃电行为监测/用电信息采集系统/高压电能采集/反窃电技术/线损计算Key words
neural network algorithm/anti-intermittent electricity stealing behavior monitoring/electric energy information acquisition system/high-voltage electric energy acquisition/anti-electricity stealing technology/line loss calculation分类
信息技术与安全科学引用本文复制引用
黄根,王大成,张辉,叶晟,莫雨阳..基于神经网络算法的反间歇性窃电行为监测方法[J].兵工自动化,2025,44(1):38-42,5.基金项目
国网上海市电力公司科技项目(B30934210001) （B30934210001）
