Design of enterprise human resource allocation model based on radial basis function neural network

Yi Wang and Lei Li

International Journal of Innovation and Sustainable Development, 2025, vol. 19, issue 3, 245-261

Abstract: In order to allocate enterprise human resources effectively and correctly, an enterprise human resources allocation model based on radial basis function (RBF) neural network is constructed. The input vector of clustering is divided by RBF neural network algorithm, the membership value of data is processed by fuzzy rules, the data category is output, and the directional connection between departments is monitored by association matrix to realise the allocation of human resources in enterprises. The experimental results show that the contribution rates of this model resource allocation planning factors is less than 85%, the mean square error results is less than 0.00914, the missed alarm rate is less than 2%, the false alarm rate is less than 1.5%. The above data prove that the model has correct and effective enterprise human resource allocation results, with good performance, high accuracy, strong anti-noise performance, high diagnostic accuracy and good practicability.

Keywords: RBF neural network; human resources; membership function; resource allocation; fuzzy rules; incidence matrix. (search for similar items in EconPapers)
Date: 2025
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