基于Stacking模型融合的专变用户电费回收风险识别方法

Identification method of electricity charge recovery risk of specialized transformer user based on Stacking model fusion

针对当前电力公司面临的专变用户电费回收风险,提出一种基于Stacking模型融合的专变用户电费回收风险识别方法。对专变用户数据进行特征处理、特征构造与特征筛选,从样本分布和特征属性上优化模型的泛化性能;利用Stacking模型融合多个基学习器,构建专变用户电费回收风险识别模型。实验结果表明,相较于其他常用的分类算法,所提方法具有更优的精确率、召回率、P-R调和均值、AUC值以及模型泛化性能,对专变风险用户的识别率也更高。

Aiming at the current electricity charge recovery risk of specialized transformer users faced by electricity companies,an identification method of electricity charge recovery risk of specialized transformer users is proposed based on Stacking model fusion.Feature processing,feature construction and feature selection are carried out for the data of specialized transformer users,and the model generalization performance is optimized from the sample distribution and feature attributes.Stacking model is used to integrate multiple base learners to construct an identification model of electricity charge recovery risk for specialized transformer users.The experimental results show that,compared with other commonly used classification algorithms,the proposed method has better precision,recall rate,P-R harmonic mean value,AUC(Area Under Curve)value,and model generalization performance,and has higher identification rate of specialized transformer risk users.