基于状态的航空发动机维修成本组合预测  

Combination forecasting model of aero-engine maintenance costs based on statistic rough sets theory

作　　者：谢庆华[1] 卢涌[1] 梁剑[2] 蒋斌[1] 张琦[3] 

机构地区：[1]解放军理工大学理学院,江苏南京211101 [2]南京航空航天大学民航学院,江苏南京210016 [3]解放军理工大学工程兵工程学院,江苏南京210007

出　　处：《解放军理工大学学报（自然科学版）》2007年第4期391-395,共5页Journal of PLA University of Science and Technology(Natural Science Edition)

摘　　要：针对发动机送修成本预估问题,在分析民用航空发动机基本维修工作的基础上,提出影响发动机维修成本的组成要素。结合航空发动机的送修特点和航空公司的实际需求,采用灰色理论,建立基于状态的发动机维修成本单一预估模型。在单一预估模型的基础上,运用统计粗集理论属性重要性判定方法,建立发动机维修成本组合预测模型。应用分析表明,组合模型较之单一预测模型在拟合和预测精度上都有明显提高,为航空公司合理制定维修计划和维修资金管理提供理论基础。In light of the limitation and shortcomings of the forecasting model using single mathematic method, a new idea of performing combination model instead of selecting model methods was proposed. The key point of a combination model was to determine the weight coefficients. Based on the rough sets theory, the uniformity of rough sets and statistical methods was employed to find out the significance of each attribute by its knowledge entropy. Then the weight coefficients could be calculated by determining the significant degree of each one. According to the experimental results, the proposed new model can obviously improve the prediction accuracy compared with the single model. This combination model has been partly adopted by airlines, which has proved helpful in reducing the airlines costs.

关 键 词：航空发动机 维修成本 统计粗集理论 灰色模型 组合模型 

分 类 号：V263.5[航空宇航科学与技术—航空宇航制造工程]