Image Model and Algorithm of Human Resource Optimal Configuration Based on FPGA and Microsystem Analysis

Abstract

Human resources are the most dynamic factor among all productivity factors. The goal of human resource management is to achieve effective and optimal allocation of resources, while the goal of optimal allocation is to promote the realization of corporate goals. At present, the overall domestic human resource management is relatively backward, and most of it is nonstandardized management, and the level of informatization and technology is not high. Therefore, this paper proposes the image model and algorithm research of human resource optimization configuration based on FPGA and microsystem analysis. First, through the data analysis method, in-depth study of traditional resource allocation algorithms: genetic algorithm and particle swarm optimization algorithm, combined with machine learning algorithms, established a human resource optimization configuration model based on FPGA and microsystem analysis, and then optimized the configuration of human resources for the impact The standard deviation and variance measurement of 18 factors of the company, as well as the analysis of the matching degree between employees and positions, and required capabilities. Finally, it is concluded that the sample average is higher and the top three are employees’ positive spirit A12, employees’ executive ability A15, and the relationship between salary and performance A11. The sample averages are 4.615, 4.522, and 4.479, respectively; standard deviation of the three factors with the smallest values are good values A8, strong employee cooperation ability A17, and perfect reward and punishment system A16. This shows that the above considerations should be considered in the optimization of enterprise human resources. Moreover, the algorithm in this paper is easier to obtain the optimal solution, and it is easier to obtain the optimal allocation result of human resources.