Application of Data Center Knowledge Graph Based on Power System Fusion Algorithm Design

Authors

  • Xin Ji Big Data Center of State Grid Corporation of China, Beijing, China, 100052
  • Chengyue Yang Big Data Center of State Grid Corporation of China, Beijing, China, 100052
  • Xiaolong Zhao Big Data Center of State Grid Corporation of China, Beijing, China, 100052
  • Linxiao Dong Big Data Center of State Grid Corporation of China, Beijing, China, 100052
  • Yuliang Zhao Big Data Center of State Grid Corporation of China, Beijing, China, 100052

Abstract

With the emergence of the Internet and the developments of science and technology, people have entered the information era where they encounter and need to analyze a significant quantity of information every day. Hence, as required by the times, the data center knowledge graph emerges, which can help people to automatically acquire knowledge from massive amounts of data. However, the research on the application of the data center knowledge graph has been confined mainly to the education domain, which has not been not conducive to the development of broader and more comprehensive applications of data center knowledge graphs. In order to help solve these problems, this article conducts a scientific and comprehensive research and analysis on the application of knowledge maps in data centers. The research results show that the robustness of HoPKG
model is 3.92% higher than RippleNet model on F1. Compared with traditional algorithms, Hermite fusion algorithm based on HoPKG model has a lower error value, which is of great significance for innovation in data center knowledge map applications.


Keywords: Data Center Knowledge Graph; Power System Fusion Algorithms; HoPKG Model; Hermite Algorithm; Back Propagation Neural Network Algorithm

Cite As

C. Yang, X. Ji, X. Zhao, L. Dong, Y. Zhao, "Application of Data Center Knowledge Graph Based on Power
System Fusion Algorithm Design", Engineering Intelligent Systems, vol. 30 no. 4, pp. 265-275, 2023.


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Published

2023-07-01

Issue

Vol. 31 No. 4 (2023): International Journal of Engineering Intelligent Systems

Section

Article

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