摘要
针对数据整合过程中屏蔽处理的异构数据较少,损耗较大的问题,提出基于大数据挖掘的电力客服中台数据智能整合方法。综合分析电力客服数据的时序性,引入大数据挖掘算法,挖掘电力中台数据,定义电力区域存在多个服务区域,聚合处理并生成电力客服逻辑区块,增加屏蔽异构数据,构建空间范围内的观测变量后,完成电力客服中台数据智能整合。搭建电力客服数据发送、接收结构,实验结果表明:所设计的数据整合方法实际产生损耗数值在20 kW左右,需要屏蔽处理的异构数据较多时,可以满足电力客服中台数据整合需求。
In the process of data integration,there are few heterogeneous data to be shielded and the data loss is large.This paper proposes an intelligent data integration method based on big data mining for power customer service.The time sequence of power customer service data is analyzed comprehensively.The big data mining algorithm is introduced to mine the power middle station data.Multiple service areas are defined in the power area.The power customer service logic block is aggregated and generated.The heterogeneous data is shielded.After the observation variables in the space are constructed,the intelligent integration of power customer service middle station data is completed.The experimental results show that the actual loss value of the designed data integration method is about 20 kW,when there are many heterogeneous data that need to be shielded,it can meet the needs of data integration in power customer service.
作者
胡学强
HU Xue-qiang(China Southern Power Grid Digital Grid Research Institute Co.,Ltd.,Guangzhou 510000 China)
出处
《自动化技术与应用》
2023年第3期117-121,共5页
Techniques of Automation and Applications
关键词
大数据挖掘
中台数据
智能整合方法
Big Data Mining
central station data
smart integration mothod
