基于BP神经网络的人力资源需求预测

Human resources demand forecast based on back-propagation neutral network

鉴于组织人力资源需求系统的复杂性和非线性的特征,分析了BP神经网络方法在人力资源需求预测中的应用,阐述了其基本原理和模型并结合实例提出了完整的实施流程.该预测方法具有很强的学习能力,各连接权重由网络通过学习自主生成,因此预测结果更具客观性和准确性,从而在很大程度上提高管理者的决策水平,对实际操作和应用具有一定的指导作用.

In view of the complexity and non-linearity of the organization＇s human resources demand system, the application of the back-propagation artificial neutral network in the human re- sources demand forecast is analyzed and its basic principle and typical model are introduced. And then the integrated implementary process through an instance is proposed. This method for forecasting has a very powerful learning capability. In addition, the weight of every link is generated by network learning automatically. Consequently, the result is more objective and accurate. That should bring some reference values to improve managers＇ decision-making level greatly. Hopefully, the study could be of help to some organizations and managers.