Abstract
At present, the economics and social developments show the characteristics of diversification, and the focus of social enterprise management is driven by the allocation of human resources. Human resource allocation is a way of appropriate allocation and reasonable placement of human resources. It means that, under the guidance of science, human resources can maintain the best combination with other resources at any time. Nevertheless, the irregularities in management teams and the balanced differences of talent quality have a great effect on the balanced development of an enterprise. Based on this, this paper studies the establishment of a recurrent neural network (RNN) model to realize the allocation of human resources and the balanced development of enterprise management. Firstly, a deep learning model, based on the recurrent neural network, is established. Then, the human resources data is analyzed to calculate the matching degree between the human resources and posts. Finally, personnel scheduling is carried out according to the matching degree score between the human resources and posts, to obtain the optimal balanced allocation result of the human resources. Experimental results show that our method can bring significant improvements to personnel position matching and effectively enhance the efficiency of human resource allocation based on the cloud environment.
Highlights
The economics and social developments show the characteristics of diversification, and the focus of social enterprise management is driven by the allocation of human resources
This paper studies the establishment of a recurrent neural network (RNN) model to realize the allocation of human resources and the balanced development of enterprise management
E formulation and implementation of human resource management policies are not effective, which has seriously affected the operation of modern enterprises. erefore, the scientific and reasonable human resource allocation method is the sword of enterprise management
Summary
Human resource allocation is the corresponding recommendation and mapping between the human resources and posts. e application of the suggested recommendation algorithm can solve the problems described in this paper. In the deep learning model, the historical records of platform users can be regarded as a periodic series of data [14, 15] To analyze these time series data, various methods based on recurrent neural network (RNN) are preferred in the existing state-of-the-art literature [16]. After several updates and iterations, their applications have been widely used in both video and music recommendation, better match the user and system data, and recommend a better individual matching mode as compared to what was already available in the market Applying this recommendation algorithm to job recommendations can complete the systematic, reasonable, and unbiased deployment of human resources. The recurrent neural network model is used to learn the post manpower matching set and obtain a deeper post preference representation containing more useful information. is information can be used for the subsequent recommended posts and manpower matching
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