基于改进灰色关联的电力企业人力资源需求预测方法

A Prediction Method for Human Resource Demand in Electric Power Enterprises Based on Improved Grey Correlation

为了研究电力企业人力需求,采用灰色关联法分析企业人力资源需求因素。考虑传统灰色关联法在预测过程面临精度低等问题,引入粒子群优化的支持向量机构建智能化预测模型,将灰色关联法获取的主要因素作为输入,实现对企业人力需求的预测。在管理部门预测比较中,2019年6月该部门实际需求人数为8人,所提方法预测需求人数与实际一致,而另外2种方法预测存在误差,可见所提技术具有出色应用效果,能够为电力企业人才的管理与企业信息化检测提供技术参考。

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 enterprise 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 other 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.