基于人工智能技术的电力信息系统运维数据整合方法

Method for Integrating Operation and Maintenance Data of Electric Power Information System Based on Artificial Intelligence Technology

传统电力信息系统运维数据整合方法数据整合时间较长,且整合过程中数据覆盖率不高,为此文章设计了基于人工智能技术的电力信息系统运维数据整合方法。首先设定统一电力信息系统运维数据整合标准与数据分类原则,根据数据间相互关系定义数据类型,分类处理电力信息系统运维数据,并剔除分类后格式不一致和重复数据,以此降低无效数据干扰、提升数据整合效率。然后制定统一编码标准,对分类后数据进行校核与编码,确定分类后的数据集与实际数据是否匹配,以离线数据为基础,利用深度学习算法进行电力信息系统运维数据的整合,可以降低系统中资源的占用率,从而提升有效数据的覆盖率。实验证明,该数据整合方法相较传统方法数据整合用时短、数据覆盖率高,具备实际应用意义。

The traditional data integration method of power information system operation and maintenance takes a long time,and the data coverage rate is low in the integration process.Therefore,a data integration method of power information system operation and maintenance based on artificial intelligence is designed.A unified data integration standard and data classification principle for operation and maintenance of power information system are given,different data types according to the relationship between data is defined,the operation and maintenance data of power information system is classified and processed,and the inconsistent and repeated data after classification is eliminated to reduce the interference of invalid data and improve the efficiency of data integration.Then a unified coding standard is established,the classified data is checked and coded,whether the classified data set matches the actual data is determined.Based on the offline data,deep learning algorithm is used to integrate the operation and maintenance data of power information system to reduce the occupancy of resources in the system and improve the coverage of effective data.Experiments show that the data integration method of this design takes less time than the traditional method,and the data coverage is high,which proves that the design method is feasible and has p ractical application significance.