Performance evaluation of supply chain cooperation for manufacturing corporations with hesitant triangular fuzzy information

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

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.