摘要
本文采用"选数据、定目标、挖数据"三步走的方法,运用目前技术已经发展成熟的大数据挖掘技术,通过对以用户为核心的稽查、业扩、电费、线损、计量、客服等相关运行信息进行有监督的机器学习,建立用户窃电预测分类模型,辅助用电检查计划的辅助编排,减少国有资产损失。
This article USES the"selected data,set goals,digging"three-step method,using the current technology has grown up in big data mining technology,through to the user as the core of the auditing,industry,electricity,line loss,metering,expanding customer service operation information related to supervised machine learning,user classification power prediction model is established,auxiliary power auxiliary inspection plan layout,reduce the loss of state-owned assets.
作者
蔡嘉荣
王顺意
吴广财
Cai Jiarong;Wang Shunyi;Wu Guangcai(Guangdong power grid co.,LTD.,Guangzhou Guangdong,510080)
出处
《电子测试》
2018年第2期108-109,共2页
Electronic Test
关键词
机器学习
用电检查
窃电预测
大数据
数据挖掘
machine learning
electricity inspection
electric inspection
data mining
big data mining
