Application Analysis of Combining BP Neural Network and Logistic Regression in Human Resource Management System

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Abstract

Human resource management involves a variety of data processing, and the process is complicated. In order to improve the effect of human resource management, this paper combines BP neural network and logistic regression analysis to construct an intelligent human resource management system and uses backpropagation learning to adjust training errors and determine connection weights. Moreover, this paper estimates the probability of a certain event through regression analysis, predicts and analyzes the human resource management process, and builds an intelligent human resource management system with the support of joint algorithms. In order to explore the reliability of the joint algorithm proposed in this paper, the effectiveness of the algorithm proposed in this paper is verified through simulation tests. The experimental research results show that the human resource management system based on BP neural network and logistic regression proposed in this paper has good practical effects.

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Xiang, T., Wu, P. Z., & Yuan, S. (2022). Application Analysis of Combining BP Neural Network and Logistic Regression in Human Resource Management System. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/7425815

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