基于灰色BP神经网络的员工需求预测

人员配置直接影响企业的生产经营活动，一份科学合理的员工需求预测对企业的作用不言而喻。以某制造业为研究对象，搜集整理2005—2017年数据。利用SPSS做相关性分析，选取固定资产、开发支出等6项员工需求影响因素。运用灰色BP神经网络理论，预测未来3年员工需求。结果表明：灰色BP神经网络比灰色预测模型具有更高的精确度；虽然灰色BP神经网络具有较高的精确度，但其结果受参数影响较大，如何确定参数则是未来研究的一个方向；灰色BP神经网络的预测结果对企业招聘、员工关系管理等模块具有一定的指导意义。

Prediction of Employee Demand Based on the Grey BP Neural Network

The personnel allocation has a direct impact on the production and operation activities of enterprises. A scientific and reasonable forecast of employee demand is self-evident to the role of enterprises. Taking a manufacturing industry as the research object, the data from 2005 to 2017 were collected and collated. SPSS was used to do the correlation analysis, and six factors affecting employee demand, such as the fixed assets, development expenditure, were selected. The grey BP neural network theory is used to forecast the employee demand in the next three years. The results show that: the grey BP neural network has higher accuracy than the grey prediction model; although the grey BP neural network has higher accuracy, its results are greatly affected by parameters, and how to determine parameters is a direction of future research; the forecasting result of grey BP neural network has certain guiding significance for the enterprise recruitment, employee relationship management and other modules.