Human resource management model based on three-layer BP neural network and machine learning

Issue title: Complex evolutionary artificial intelligence in cognitive digital twinning

Guest editors: Neal Wagner, Sundhararajan, Le Hoang Son and Meng Joo

Article type: Research Article

Authors: Wei, Guohua^{a; *} | Jin, Yi^b

Affiliations: [a] Liaocheng University, Liaocheng, Shandong, China | [b] Liaocheng Hospital of Traditional Chinese Medicine, Liaocheng, Shandong, China

Correspondence: [*] Corresponding author. Guohua Wei, Liaocheng University, Liaocheng, Shandong, China. E-mail: [email protected].

Abstract: At present, data is in a state of explosive growth. The rapid growth of data collected by enterprises has exceeded the processing capacity of traditional human resource management systems, resulting in their inability to perform data management and data analysis. In order to improve the practicality of the human resource management system, this paper applies machine learning technology to the human resource management system, selects dimensions according to the prediction method, and builds a combined model consisting of an optimized GM (1,1) model and a BP neural network model. The model is implemented by a three-layer BP neural network. In order to verify the performance of the research model, this article conducts research using an entity as an example. The research results show that the method proposed in this paper has certain practical effects and can improve the reference for subsequent related research.

Keywords: Neural network, machine learning, improved model, human resources, predictive model

DOI: 10.3233/JIFS-189226

Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2289-2300, 2021