电测与仪表2016，Vol.53Issue(z1)：111-114,4.
电力客户用电行为特征挖掘与预测
Characteristics mining and prediction of electricity customer's behavior
杨一帆 1傅军 1朱天博 1孙志杰 1谢枫1
作者信息
- 1. 国网冀北电力有限公司电力科学研究院，北京100045
- 折叠
摘要
Abstract
In order to help the power supply company to make marketing decisions, extract electricity customer's pay-ment data, study on the characteristics mining and prediction method of electricity customer arrears based on the mass information collection of smart grid. According to the behavior of arrears customers and electricity regulations on elec-tricity charges, the electricity customer arrears are defined. The arrears data industry distribution and time distribution is analyzed, the grey correlation analysis method is applied to analyze the correlation between arrears data and industry index, method of using regression model to predict the probability of customer arrears is explored. Calculation of char-acteristics of electricity customer arrears and researching on customer arrears probability prediction method is helpful to power supply company's tariff recovery.关键词
智能电网/大数据/数据挖掘/欠费/预测Key words
smart grid/big data/data mining/arrears/prediction分类
信息技术与安全科学引用本文复制引用
杨一帆,傅军,朱天博,孙志杰,谢枫..电力客户用电行为特征挖掘与预测[J].电测与仪表,2016,53(z1):111-114,4.
