基于云计算技术的电力大数据分布式检索系统

为了提高电力大数据定位识别和信息融合能力,进行电力大数据检索优化设计,提出一种基于云计算技术的电力大数据检索系统设计方法,采用多元回归分析方法构建电力大数据库存储结构模型,进行电力大数据的分布式存储数据结构特征分析,对混合型的电力大数据在云计算环境下进行信息聚类融合处理,采用模糊特征分组聚类方法对不同属性的电力大数据进行分组检测,提取电力大数据的关联规则特征量,采用云计算技术实现电力大数据分布式检索。在嵌入式环境下进行电力大数据分布式检索系统软件设计。仿真结果表明,采用该方法进行电力大数据检索的特征指向性较好,数据检索的数据召回率较高。

Distributed Retrieval System of Power Big Data Based on Cloud Computing Technology

In order to improve the capability of power big data location identification and information fusion, this paper proposes a design method of power big data retrieval system based on cloud computing technology. The multivariate regression analysis method is used to construct the storage structure model of large electric power database, and to analyze the distributed storage data structure characteristic of power big data. In the cloud computing environment, the hybrid power big data is processed through information clustering fusion, and the power big data with different attributes is detected by using fuzzy feature clustering method. The paper extracts the association rule feature of power big data and realizes power big data distributed retrieval by cloud computing technology. The software design of the power big data distributed retrieval system is carried out in an embedded environment. The simulation results show that the proposed method has good characteristic directivity and high precision and recall rate for power big data retrieval.