小波神经网络在反窃电系统中的应用研究
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引用本文:石盼?覮,张合川,赵明星,周国亮,徐相波.小波神经网络在反窃电系统中的应用研究[J].计算技术与自动化,2020,(3):44-48
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作者单位
石盼?覮,张合川,赵明星,周国亮,徐相波 (国网冀北电力有限公司 技能培训中心(保定电力职业技术学院)河北 保定071051) 
中文摘要:针对目前窃电现象普遍存在及反窃电工作难度越来越大的现状,为有效检测评估用户的用电状态,通过对用户用电信息数据的处理和分析,提取出相应的指标来构建指标评价体系。在对小波神经网络初值的设置和训练更新的策略进行改进的基础上,提出了一种基于改进小波神经网络的反窃电系统数学模型,从而获得用户窃电的嫌疑因子和窃电方式,并通过与其它网络模型在反窃电系统实例的对比分析验证了本文方法的有效性和优越性。本研究成果可为电力公司的反窃电工作提供有效的理论参考和技术指导。
中文关键词:小波神经网络  反窃电  指标评价体系  窃电嫌疑因子
 
Application Research of Wavelet Neural Network in Anti-theft System
Abstract:In view of the widespread phenomenon of electric larceny and the increasing difficulty of anti-larceny work at present,in order to effectively detect and evaluate the power consumption status of customers,through the processing and analysis of user electricity information data,the corresponding indexes are extracted to construct the index evaluation system,based on the improvement of the initial value setting and training updating strategy of wavelet neural network,a mathematical model of anti - theft system based on improved wavelet neural network is proposed,thus the suspected factors and ways of stealing electricity are obtained,the effectiveness and superiority of the proposed method are verified by comparing with other network models in the anti-stealing power system. The research results can provide effective theoretical reference and technical guidance for the anti-stealing work of electric power companies.
keywords:wavelet neural network  anti-electricity stealing  indictor evaluation system  power theft suspicion coefficient
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