火力与指挥控制2024，Vol.49Issue(12)：55-61,7.DOI:10.3969/j.issn.1002-0640.2024.12.006
改进灰色马尔科夫模型及其在航空备件需求预测中的应用
Improved Gray Markov Model for Demand Forecasting of Aviation Spare Parts
摘要
Abstract
In response to the low prediction accuracy of the traditional Gray Markovmodel and its inability to quantify the strength of state relationships,an improved Gray Markov forecast-ing model for aviation spare parts is proposed.The model improves the solution of the traditional gray model's background value by usinga combination interpolation method.Additionally,the model continuously updates historical data through a metabolic method,reducing the averagerela-tive error from 3.2%to 2.17%.The model's posterior error coefficient(C)is 0.004.with a small error probability(p)greater than 0.8,indicating a good level with highprediction accuracy.Finally,the weighted Markov model is used to correct the forecasted values from the metabolic model.After correction,the relative error ofthe demand forecast for 2015 decreased from-4.04%to-2.82%.关键词
航空备件/背景值改进/新陈代谢/灰色预测/加权马尔科夫Key words
aviation spare parts/background value improvement/metabolism/gray forecast/weighted markov分类
航空航天引用本文复制引用
廖乃智,涂继亮,刘辉,邓泽平,赖国超..改进灰色马尔科夫模型及其在航空备件需求预测中的应用[J].火力与指挥控制,2024,49(12):55-61,7.基金项目
国家自然科学基金(72261027) （72261027）
南昌航空大学校级研究生创新专项基金资助项目(YC2023-026) （YC2023-026）
