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Copyright © 2022 Suihai Chen. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

With the vigorous development of China’s market economy, a new generation of artificial intelligence technology has also developed rapidly, which has strongly promoted the optimization and improvement of China’s electrical automation control system. The use of artificial intelligence technology in power automation systems mainly has the following two advantages: it can reduce the manufacturing time of power products, thereby increasing the number of workers manufacturing power products and promoting enterprises to conduct larger-scale machine manufacturing, thereby improving the comprehensive economic benefits of enterprise machine manufacturing, but also improve the quality of manufactured products of electric power products. Since the machine control of artificial intelligence is more efficient than manual manufacturing, it reduces the manufacturing problems caused by the subjective factors of manufacturing workers to a certain extent and thus improves the qualification rate of machine production. Electrical engineering plays an important role in China’s urban development, and automatic control is an important part of electrical engineering, which can have a direct impact on the quality of electrical engineering. Therefore, in order to promote the healthy development of cities in China, this paper studies the application of artificial intelligence technology in electrical engineering automation by analyzing relevant data, in order to provide a reliable basis for relevant personnel to carry out their work.

Details

Title
Application and Thinking of Artificial Intelligence in Electrical Automation
Author
Chen, Suihai 1   VIAFID ORCID Logo 

 Universiti Malaysia Sarawak (UNIMAS), 94300, Malaysia 
Editor
Kuruva Lakshmanna
Publication year
2022
Publication date
2022
Publisher
John Wiley & Sons, Inc.
e-ISSN
15308677
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2696742924
Copyright
Copyright © 2022 Suihai Chen. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.