基于灰色马尔可夫模型的装备维修备件需求预测

Spares Demand Prediction of Equipment Maintenance Based on Grey Markov Model

针对武器装备维修备件需求量预测的难点,在全面分析各种预测方法的基础上,根据武器装备维修备件需求量是典型的小子样和贫信息的特点,在灰色GM(1,1)模型的基础上建立了灰色马尔可夫模型,并通过具体的实例进行验证,结果表明,灰色马尔可夫模型对具有随机性和波动性的非平稳随机序列具有很好的拟合效果,为武器装备维修备件需求量预测提供了一种新的途径和方法。

Aimed at the difficulties of spares demand prediction for weapons and equipments maintenance, based on comprehensive analysis of the various predicting methods,according to the features of weapons and equipments maintenance spares that were typically small sample and poor information,the grey Mark-ov model was established based on the GM （1,1）model,and the model was verified by use of a specific example.The results showed that the grey Markov model has a very good fitting effect for randomness and waviness of non-stationary random sequence.Thus the model can provide a new approach to predict the spares demand for weapons and equipments maintenance.