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林树青, 白敏, 陈永发. 基于供电所历史电费数据的用户风险评估[J]. 农村电气化, 2024, (5): 15-18. DOI: 10.13882/j.cnki.ncdqh.2024.05.004
引用本文: 林树青, 白敏, 陈永发. 基于供电所历史电费数据的用户风险评估[J]. 农村电气化, 2024, (5): 15-18. DOI: 10.13882/j.cnki.ncdqh.2024.05.004
LIN Shuqing, BAI Min, CHEN Yongfa. User Risk Assessment Based on Historical Electricity Bill Data of Power Supply Stations[J]. RURAL ELECTRIFICATION, 2024, (5): 15-18. DOI: 10.13882/j.cnki.ncdqh.2024.05.004
Citation: LIN Shuqing, BAI Min, CHEN Yongfa. User Risk Assessment Based on Historical Electricity Bill Data of Power Supply Stations[J]. RURAL ELECTRIFICATION, 2024, (5): 15-18. DOI: 10.13882/j.cnki.ncdqh.2024.05.004

基于供电所历史电费数据的用户风险评估

User Risk Assessment Based on Historical Electricity Bill Data of Power Supply Stations

  • 摘要: 电费作为供电企业经营成果的直接体现,因此加强电费管理、减轻电费风险显得尤为重要。精准高效的电费智能催收应用可以有效地建设电费回收风险,随着大数据、云计算等新技术的快速发展,电力用户画像库的建设和应用已具备充分条件。基于历史数据,提炼用户特征标签,多维度呈现用户画像,并筛选营销电费回收风险的特征指标,对电费回收方式预测,判断用户的电费预测风险等级,提高电费催收效率。

     

    Abstract: As the direct embodiment of the operating results of power supply enterprises, it is particularly important to strengthen the management of electricity charges and reduce the risk of electricity charges. Accurate and efficient electricity bill intelligent collection application can effectively build electricity bill recovery risk, with the rapid development of new technologies such as large data and cloud computing, the construction and application of electricity customer portrait library has sufficient conditions. Based on historical data, extract customer characteristic labels, present customer portraits in multiple dimensions, and screen the characteristic indicators of marketing electricity rate recovery risk, predict the way of electricity rate recovery, judge the risk level of users' electricity rate prediction, and improve the efficiency of electricity rate collection.

     

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