基于统计粗集的航空发动机维修成本组合预测模型

维修成本是航空发动机使用单位实现降耗增效关注的重点之一。釆用灰色理论，建立基于状态的发动机维修成本单ー预估模型，在单ー预估模型的基础上，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，这种组合预测方法充分利用统计粗集理论“让数据说话”的优势。应用分析表明，组合模型较之单ー预测模型在拟合和预测精度上都有明显提高，这种方法也为发动机使用单位合理制定维修计划和维修资金管理提供理论基础。

The Combination Forecasting Model of Aero-engine Maintenance Cost Based on Statistic Rough Set Theory

Airlines pay closed attention to maintenance cost for efficiency improvement and fuel consumption reduction. As the limitation and shortcoming of forecasting model using single mathematic method, a new idea of performing combination model instead of selecting model methods was proposed. A key point of combination model is to determine the weight coefficients. Based on the rough set theory, it employs the uniformity of rough sets and statistical methods 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 than the single model. This combination model has been partly adopted by airlines, which has proved helpful in reducing the airlines cost.