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

IF 1.1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS EAI Endorsed Transactions on Scalable Information Systems Pub Date : 2023-08-18 DOI:10.4108/eetsis.3747
Le Zhang, Juanyin Liu, Xia Feng, Yan Li, Le Mei Zhu
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Abstract

INTRODUCTION: Robotics is currently the most cutting-edge international science and technology, as well as a high-value-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.
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基于机器人控制系统设计的民办高校毕业生就业意向影响因素研究
机器人技术是目前国际上最前沿的科学技术,也是一项高附加值的核心技术。机器人广泛应用于各种工业领域,作为机器人技术发展的新方向,对解决当前中国的就业问题发挥着重要作用。目的:结合其研究成果,在机器人控制系统中引入机器学习方法,结合就业因素与环境关系分析,建立机器人工作环境中的就业指标体系。方法:结合其研究成果,在机器人控制系统中引入机器学习方法,结合就业因素与环境关系分析,建立机器人工作环境中的就业指标体系。结果:研究发现,随着受教育程度的提高,大学生择业意愿逐渐增强;受教育程度越低,找工作的意愿越弱;受教育程度越高,他们对教育质量和教育专业越敏感,他们的工作意愿越高。结论:基于机器人控制系统设计,现实经济活动中对环境有影响的因素(如年龄、性别、职业、受教育程度等)对未来机器人技术在中国的应用和发展起到促进作用。
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来源期刊
EAI Endorsed Transactions on Scalable Information Systems
EAI Endorsed Transactions on Scalable Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.80
自引率
15.40%
发文量
49
审稿时长
10 weeks
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