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Factors influencing the employment intention of private college graduates based on robot control system design.

Authors :
Le Zhang
Juan Liu
Xia Feng
Yan hui Li
Le mei Zhu
Source :
EAI Endorsed Transactions on Scalable Information Systems; 2023, Vol. 10 Issue 5, p1-10, 10p
Publication Year :
2023

Abstract

INTRODUCTION: Robotics is currently the most cutting-edge international science and technology, as well as a highvalue-added core technology. Robots are widely used in a variety of industrial fields, as a new direction in the development of robotics, and play an important role in solving the current employment problems in China. OBJECTIVES: This paper combines its research results, introduces the machine learning method in the robot control system, and establishes the employment index system in the robot working environment by combining the employment factors with the environmental relationship analysis. METHODS: This paper combines its research results, introduces the machine learning method in the robot control system, and establishes the employment index system in the robot working environment by combining the employment factors with the environmental relationship analysis. RESULTS: The study found that the willingness of university students to choose a job gradually increases as their education level rises; the lower the level of education, the weaker their willingness to look for a job; the higher the level of education the more sensitive they are to the quality of education and educational specialities, the higher their willingness to work. CONCLUSION: Based on the robot control system design the factors that have an impact on the environment in real economic activities (e.g., age, gender, occupation, education level, etc.) play a role in promoting the future application and development of robotics in China. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20329407
Volume :
10
Issue :
5
Database :
Complementary Index
Journal :
EAI Endorsed Transactions on Scalable Information Systems
Publication Type :
Academic Journal
Accession number :
171946912
Full Text :
https://doi.org/10.4108/eetsis.3747