Application of Automatic Completion Algorithm of Power Professional Knowledge Graphs in View of Convolutional Neural Network

Abstract

With the continuous development of electric power informatization, a large amount of electric power data information has been produced. The reasonable application of electric power database is of great significance. Building the automatic completion optimization algorithm of knowledge graphs (KGs) in power professional field provides a method to extract structured knowledge from a large number of power information and images, which has broad application value. The automatic completion algorithm of power professional KGs in view of convolutional neural network (CNN) is conducive to completing the analysis and management of power data, enabling the flexible use of data information generated by the power grid, and bringing ideas for the in-depth exploration and innovation of power grid data information application.