Construction of Digital Transformation Management System for Power Grid Enterprises Based on Artificial Intelligence Algorithm

Authors

  • Xiaoguang Liu Gansu Tongxing Intelligent Technology Development Co., LTD., Lanzhou 730050, Gansu, China
  • Xi Cai Gansu Tongxing Intelligent Technology Development Co., LTD., Lanzhou 730050, Gansu, China
  • Jianfeng Han Gansu Tongxing Intelligent Technology Development Co., LTD., Lanzhou 730050, Gansu, China

Abstract

The application of digitalization has transformed the lives of individuals as well as the operational aspects of public and private sectors. In particular, it has led to the construction of digital management systems for many enterprise-management models. At present, the application of digitization in enterprise management is increasing, and advanced methods and technologies are being used to gather and display information. This paper aims to achieve the digital transformation of the power grid enterprise management system in the artificial intelligence environment. It draws on the principles and laws of artificial intelligence to construct and optimize the management system of the digital model, and achieve the digital transformation of enterprises as a development strategy. In a survey of employees, which sought their opinions on the management system after the transformation, 63.62% of respondents believed that the current new management system was very effective, 23.73% thought it was average, and the remaining 12.65% thought it was not very effective. Therefore, it is very important to build a digital management system for the future development of power grid enterprises.

Keywords: enterprise management system, digital transformation, artificial intelligence algorithm, data acquisition algorithms

Cite As

X. Liu, X. Cai, J. Han, "Construction of Digital Transformation Management System for Power Grid Enterprises Based on Artificial Intelligence Algorithm", Engineering Intelligent Systems, vol. 31 no. 2, pp. 153-164, 2023.







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Published

2023-03-01

Issue

Vol. 31 No. 2 (2023): International Journal of Engineering Intelligent Systems

Section

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