Artificial intelligence-based organizational human resource management and operation system - Yang, Yang (Frontiers in Psychology, 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. 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 towards a more scientific and reasonable method. 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 system. 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. This article uses GAE data storage area, the storage performance and query performance of the human resource management system can be greatly optimized. 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.