改进的马尔科夫模型在人力资源预测中的应用

人力资源的需求预测是企业发展中的重大问题。由于企业的人力资源管理政策在一定的时间内是稳定不变的,因此很多企业在预测未来的人力需求时往往采用马尔科夫转移矩阵模型。但是由于模型的局限性,和企业人力的因辞职、退休、开除等原因退出企业,造成预测的数据偏小,无法满足企业的需求。文章采用了灰色GM（1,1）模型来进行改进,并考虑了企业的战略发展要求,解决了马尔科夫模型的数据偏小缺限,具有较好的预测结果。

Improved Markov Model Application in Human Resources Forecast

Human resources demand forecast was the important problem for enterprise development. Because Enterprise human resources management policy was stable, many enterprises used Markov transfer matrix model to forecast future human resources demands. Because of the boundness of the model and resignation, retirement and dismissed in the enterprise, which caused small data in the forecast, could not meet the needs of the enterprise. The thesis adopted grey GM （ 1,1 ）model lo get improvement, considering the strategic development of the enterprise requirements, solved Markov defects of small dater, with good forecast results.