海军航空兵机动转场备件携带量预测模型研究

摘要

When naval aviation does transportation,the calculation of airliner spares demand is essential, but the lack of quantitative analysis method of calculating precise data exists today. This paper gave an improved gray Markov chain model used to predict the number of airliner spares to carry. This model uses high- order interpolation to generate the data sequence,and the introduction of close correlation to improve the state division of Grey Markov chain methods. Example calculations show that the model can improve accuracy of forecasting the number of airliner spares to carry.%针对海军航空兵转场时所携行航材备件需求量缺乏定量分析和精确数据计算方法的情况,提出了一种改进的灰色马尔可夫链模型用于预测备件携带数量.模型采用高次插值生成数据序列,并引入接近关联度改进灰色马尔可夫链状态划分方法.实例计算结果表明,该模型可提高预测备件携带数量预测精度.