基于随机森林的权力用户肖像模型

IF 1.7 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS IET Cyber-Physical Systems: Theory and Applications Pub Date : 2023-06-02 DOI:10.1049/cps2.12063
Di Yang, Ming Ji, Yuntong Lv, Mengyu Li, Xuezhe Gao
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引用次数: 0

摘要

随着能源互联网的蓬勃发展,各类用户信息数据与日俱增。如何全面深入挖掘用户的有效信息,建立模型预测大数据用户的行为特征,区分客户关系,为各类平台用户的下一步行为提供准确依据,成为用户行为大数据分析的研究热点之一。根据权力用户的特征向量对数据进行采样。对权力用户进行画像挖掘,利用模型中决策树节点纯度的度量进行用户筛选和分析。生成上下停止规则的决策树变量。然后对模型和物流模型的结果进行测试和分析,结果表明该模型能有效预测电力用户的行为。通过分析根据用电行为特征提出的用户策略,验证了方案的有效性。实例表明,该模型比传统的物流模型具有较强的区分能力和良好的稳定性,能有效地提前预测用户行为,减少用户投诉,有利于企业和用户形成互利互惠的长效机制,具有很强的现实意义。本文通过电力大数据技术分析用户全景,提出用户用电优先级评估成熟度模型。强调利用电力大数据技术包中提供的资源和方法解决用户用电的实际问题,帮助电力企业规避市场风险,提高服务水平,具有很强的现实意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Power user portrait model based on random forest

With the vigorous development of the energy Internet, all kinds of user information data are increasing day by day. How to comprehensively and deeply mine the effective information of users, develop a model to predict the behaviour characteristics of big data users, distinguish customer relationships, and provide an accurate basis for the next behaviour of users for various platforms have become one of the research hotspots of big data analysis of user behaviour. The data is sampled according to the feature vector of power user. The portrait mining of power user is conducted, and the user screening and analysis are conducted by using the measure of decision tree node purity in the model. The decision tree variable of the up–down stopping rule is generated. Then the results of the model and the Logistics model are tested and analysed, which can effectively predict the behaviour of power user. The proposed user strategy based on the characteristics of power consumption behaviour is analysed to verify the effectiveness of the scheme. The example shows that the model has a strong ability to distinguish and good stability than the traditional Logistics model, which can effectively predict the user's behaviour in advance, reduce user complaints, and help enterprises and users to form a long-term mechanism of mutual benefit and reciprocity, which has a strong practical significance. This paper analyses the panorama of users through power big data technology and proposes a maturity model to evaluate the priority of users' electricity consumption. It emphasises the use of resources and methods provided in the power big data technology package to solve the practical problems of users' electricity consumption, and helps power companies to avoid market risks and improve service levels, which has strong practical significance.

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来源期刊
IET Cyber-Physical Systems: Theory and Applications
IET Cyber-Physical Systems: Theory and Applications Computer Science-Computer Networks and Communications
CiteScore
5.40
自引率
6.70%
发文量
17
审稿时长
19 weeks
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