摘要
电力工程数据分析与应用,是实现大规模电力工程缺失数据筛选、进行形态分析的基础。文章针对电力工程缺失数据筛选困难的问题,提出了一种基于密度聚类算法的分析方法,该方法通过电力工程数据收集、预处理、提取数据个性化特征以及进行密度聚类算法分析等步骤,实现了电力工程缺失数据的高速筛查和形态分析。文章通过智能仪表、智能终端数据同步性验证,认为所提出的基于密度聚类算法的电力工程数据完整性分析方法能够有效实现缺失数据筛查和形态分布解读,对于全面提升电力我国电力工程数据完整性和用电情况分析具有较好的指导意义。
Data analysis and application of power engineering are the basis of missing data screening and morpho⁃logical analysis in large-scale power engineering.In view of the lack of power engineering data screening difficult problem,this paper proposes a algorithm based on density clustering analysis method,the method by electric power engineering data collection,preprocessing,to extract data personalization features and density clustering algorithm analysis steps,to realize the high-speed screening and morphological analysis of power electrical engineering miss⁃ing data.In this paper,through the intelligent instrument,intelligent terminal data synchronization test,think of the proposed clustering algorithm based on density of electric power engineering data integrity analysis method can ef⁃fectively realize the missing data screening and morphological distribution interpretation,it has a good guiding sig⁃nificance for comprehensively improving the data integrity and power consumption analysis of power engineering in my country.
作者
唐取
毕圣灵
TANG Qu;BI Sheng-ling(Foshan Power Supply Bureau of Guangdong Power Grid Co.,Ltd,Foshan Guangdong 528000,China)
出处
《粘接》
CAS
2020年第12期74-77,共4页
Adhesion
关键词
密度聚类算法
电力工程
缺失数据筛查
特征提取
density clustering algorithm
electric power engineering
missing data screening
feature extraction
