A Prediction Method for Human Resource Demand in Electric Power Enterprises Based on Improved Grey Correlation
In order to effectively study the human resource demand of electric power enterprises,the grey correlation method is used to analyze the factors affecting the human resource demand of enterprises.Considering the low accuracy of traditional grey correlation methods in the prediction process,this paper introduces particle swarm optimization support vector machine to build an intelligent prediction model,uses the main factors obtained by grey correlation method as inputs to achieve prediction of en-terprise human resource demand.In the comparison of management department forecasts,the actual demand for the department in June 2019 is 8 people,and the proposed method predicted the demand to be consistent with the actual number,while the oth-er two methods has errors in their predictions.It can be seen that the proposed technology has excellent application effects,and can provide technical reference for talent management and enterprise information detection in electric power enterprises.
grey correlation methodelectric power enterprisesupport vector machineparticle swarm algorithmdemand pre-diction
万方数据
维普
