Yang Yang
School of Management and Economics, North China University of Water Resources and Electric Power, Zhengzhou, China.
Front Psychol. 2022 Jul 22;13:962291. doi: 10.3389/fpsyg.2022.962291. eCollection 2022.
The trend of globalization, marketization, and informatization continues to strengthen, in today's development environment, how to seize the opportunity and obtain a competitive advantage in human resources is an important issue that needs to be explored. Human resource management refers to the effective use of relevant human resources inside and outside the organization through management forms under the guidance of economics and humanistic thinking. It is a general term for a series of activities that ensure the achievement of organizational goals and the maximization of member development. With the rapid development of society and economy, the competition between enterprises has intensified. If an enterprise wants to adapt to social development, it is necessary to strengthen the internal management of the organization. The internal management also needs to rely on human resource management. The purpose of this paper is to study an organization's human resource management and operation system based on artificial intelligence. It expects to use artificial intelligence technology to design the human resource management system and to improve the quality of employees to make the enterprise develop toward a more scientific and reasonable method. It uses artificial intelligence technology to mine the relevant data of enterprises, understand the situation of enterprises in a timely manner, and adjust unreasonable rules. This paper establishes a dynamic capability evaluation model and an early warning model for human resource management and further studies the improvement approach based on human resource management. This paper analyzes the application, feasibility, and practical significance of data mining technology in human resource management systems. It focuses on the commonly used algorithms in the field of data mining and proposes specific algorithm application scenarios and implementation ideas combined with the needs of human resource management practices. The experimental results of this paper show that the average working life of incumbent employees is 3.5 years, the average length of employees who leave the company is 5 years, and some employees are 5-6 years old. From this data, it can be seen that the average number of years of on-the-job employees is short, and the work experience has yet to be accumulated.
全球化、市场化和信息化趋势不断增强，在当今的发展环境下，如何抓住机遇并在人力资源方面获得竞争优势是一个需要探索的重要问题。人力资源管理是指在经济学和人文思想指导下，通过管理形式对组织内外的相关人力资源进行有效利用。它是确保组织目标实现和成员发展最大化的一系列活动的总称。随着社会经济的快速发展，企业之间的竞争日益激烈。企业若想适应社会发展，就必须加强组织的内部管理。而内部管理也需要依靠人力资源管理。本文旨在研究基于人工智能的组织人力资源管理与运营体系。期望利用人工智能技术设计人力资源管理系统，提升员工素质，使企业朝着更科学合理的方向发展。利用人工智能技术挖掘企业的相关数据，及时了解企业状况，并调整不合理的规则。本文建立了人力资源管理的动态能力评价模型和预警模型，并进一步研究基于人力资源管理的改进方法。分析了数据挖掘技术在人力资源管理系统中的应用、可行性及实际意义。重点关注数据挖掘领域常用的算法，并结合人力资源管理实践需求提出具体的算法应用场景和实施思路。本文的实验结果表明，在职员工的平均工作年限为3.5年，离职员工的平均工作时长为5年，部分员工为5至6年。从这些数据可以看出，在职员工的平均工作年限较短，工作经验还有待积累。
