A comparative study of different prediction models in predicting human resource demands

Article type: Research Article

Authors: Huang, Bo

Affiliations: Civil Aviation Flight University of China, Guanghan, Sichuan, China | E-mail: [email protected]

Correspondence: [*] Corresponding author: Civil Aviation Flight University of China, Guanghan, Sichuan, China. E-mail: [email protected].

Abstract: This study analyzed three prediction models: ID model, GM (1,1) model and back-propagation neural network (BPNN) model. Firstly, the principles of the three models were introduced, and the prediction methods of the three models were analyzed. Then, taking enterprise A as an example, the demand for human resources was predicted, and the prediction results of the three models were compared. The results showed that the maximum and minimum errors were 240 people and 12 people respectively in the prediction results of the ID3 model and 64 people and 37 people respectively in the prediction results of the GM (1, 1) model; the errors of the BPNN model were smaller than ten people, and the minimum value of the BPNN model was three people, which was in good agreement with the actual value. The prediction of the human resource demand of enterprise A in the future five years with the BPNN model suggested that the demand for employees would growing rapidly. The results show that the BPNN model has better reliability and can be popularized and applied in practice.

Keywords: Human resource, prediction, grey prediction, neural network

DOI: 10.3233/JCM-215788

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 2, pp. 541-551, 2022