Predicting the Reasons of Employee Turnover Based on BP Neural Network Model

Abstract

Employee turnover is related to the survival and development of enterprise team, which increases the cost of human resources and causes management difficulties and economic losses. Bp neural network model can deal with nonlinear problems, large-scale data and complex pattern recognition tasks, and plays an important role in the field of prediction. In this paper, BP neural network model is used to deeply analyze the causes of employee turnover, and deeply predict the causes of complex employee turnover with economic development and post-epidemic era. Through training and learning of relevant data of employee turnover, BP neural network can extract potential patterns and rules of employee turnover, so as to predict the trend of employee turnover in the future. So that enterprises can better understand the demands and expectations of employees, formulate more reasonable policies and plans, improve the job satisfaction and loyalty of employees, and reduce the employee turnover rate. Provide guidance for enterprise management's decision-making and rectification.