Construction of an Intelligent Salary Prediction Model and Analysis of BP Neural Network Applications

Salary prediction has always been a crucial topic in human resource management, yet current prediction models exhibit certain limitations, necessitating more intelligent methods for optimization and enhancement. This paper aims to construct an intelligent salary prediction model and apply the BP Neural Network for analytical purposes to enhance the accuracy and reliability of salary predictions. To achieve this, we employed the BP Neural Network, a deep learning algorithm, rigorously validated and analyzed through extensive empirical research. The findings demonstrate that the BP Neural Network achieves higher accuracy and stability in salary prediction, effectively improving the level of prediction. This research not only offers a more intelligent salary prediction model for the field of human resource management, providing more precise references for business decision-making but also paves new theoretical and practical avenues for the application of deep learning algorithms in human resource management.