电测与仪表2024，Vol.61Issue(1)：107-112,6.DOI:10.19753/j.issn1001-1390.2024.01.016
基于局部线性嵌入和深度森林算法的电力客户投诉预测模型
Power customer complaint prediction model based on local linear embedding and deep forest algorithm
张梅 1保富1
作者信息
- 1. 云南电网有限责任公司信息中心,昆明 650217
- 折叠
摘要
Abstract
Due to the increasingly fierce competition in the electricity market,requirements of clients for service quality are constantly improving,and the number of complaints of clients continues to rise.Based on the architecture of the power customer complaint prediction model based on big data,a power customer complaint prediction method based on local lin-ear embedding and deep forest algorithm is proposed in this paper.The local linear embedding algorithm is used to reduce the dimensionality of the input feature vectors of the customer complaint prediction model to reduce the computation and a-void falling into the local optimum solution.The dimensionality reduced feature vector of complaint prediction is scanned with multi-granularity to improve its representational learning ability.The deep forest algorithm model is established based on the cascade forest to realize the complaint prediction of customers.The simulation results of actual data show that,compared with no dimensionality reduction processing and other prediction models,the prediction model proposed in this paper can more accurately predict the trend of customer complaints,which provides a reference for the analysis and pre-diction of customer complaints by power companies.关键词
电力客户/投诉预测模型/局部线性嵌入/深度森林算法Key words
power customer/complaint prediction model/local linear embedding/deep forest algorithm分类
信息技术与安全科学引用本文复制引用
张梅,保富..基于局部线性嵌入和深度森林算法的电力客户投诉预测模型[J].电测与仪表,2024,61(1):107-112,6.
