基于多源数据过滤分析的电力大数据智能高效分析挖掘技术研究

Zhengxiong Mao, Fu Bao, Yuan Tian, Hang Zhang
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引用次数: 2

摘要

针对电力行业数据量不断增加,数据分析难度越来越大的现状,设计一种智能高效的电力大数据分析挖掘框架,快速获取有价值的信息。分析电力大数据中心的总体框架,主要包括服务层、验证层、数据源层和特征分析层。此外,通过对数据挖掘过程的分析,发现业务需要加强和实现扩展。电力大数据智能分析与挖掘技术框架设计主要包括电力市场需求、客户分析、高性能数据分析、服务体系、数据安全治理等模块。通过对智能电力大数据挖掘实例的分析,分析结果表明,智能电力数据挖掘具有良好的分析效果和较高的挖掘精度
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Research on intelligent and efficient analysis and mining technology of power big data based on multi-source data filtering analysis
In view of the increasing data volume and the increasingly difficult data analysis in the power industry, an intelligent and efficient analysis and mining framework for power big data is designed to quickly obtain valuable information. Analyze the overall framework of the power big data center, mainly including the service layer, verification layer, data source layer, and feature analysis layer. In addition, through analyzing the process of data mining, it is found that the business needs to be strengthened And realize expansion. The framework design of power big data intelligent analysis and mining technology mainly includes power market demand, customer analysis, high-performance data analysis, service system, data security governance and other modules. Through the analysis of an example of intelligent power big data mining, the analysis results show that the intelligent power data mining has good analysis effect and high mining accuracy
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