文档介绍：2010-12题录英译集
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基于偏最小二乘回归分析的试验装备修理成本预测
张翀1,郑绍钰2,王璐璐3
(1. 装备指挥技术学院研究生管理大队,北京 101416;2. 装备指挥技术学院装备采办系,北京 101416;
3. 中国民航大学电子信息工程学院,天津 300300)
摘要:为了科学预测试验装备修理成本,提高维修经费决策质量,引入偏最小二乘回归分析(Partial Least Squares Regression, PLSR)对试验装备修理成本进行预测。针对试验装备修理成本小样本、贫数据、特征量相关性强的不利条件,构建预测模型;基于以往数次大修相关数据,预测试验专用装备使用期的某次大修成本。同时,为保持模型的稳健性,提高模型解释能力和预测精确度,尝试利用变量投影重要性分析对模型进行优化,取得了较好的效果。实例证明,该方法不仅能在多变量间存在严重多重相关性情况下建立模型,而且能够有效筛选与因变量关系不大的自变量,简化输入样本集。
关键词:偏最小二乘回归分析;试验装备;修理成本;预测;变量投影重要性分析
Forecast of Tentative Equipment Repair Cost Based on Partial Least Squares Regression
Zhang Chong1, Zheng Shaoyu2, Wang Lulu3
(1. Administrant Brigade of Postgraduate, Institute mand & Technology of Equipment, Beijing 101416, China;
2. Dept. of Equipment Acquisition, Institute mand & Technology of Equipment, Beijing 101416, China;
3. College of Electronic Information Engineering, Civil Aviation University of China, Tianjin 300300, China)
Abstract: In order to forecast tentative equipment’s repair cost scientifically, and improve the decision-making quality of maintenance outlay, partial least squares regression (PLSR) is introduced to forecast tentative equipment’s repair cost. Aiming at the limitation of tentative equipment repair cost’s small sample, inadequate statistics, close relative eigenvector, forecasting model is constructed; based on several heavy repair data before, the heavy repair cost of special tentative equipment in use is forecasted. Meanwhile, it has the good effect to attempt optimizing the model by using variable importance in projection (VIP) in order to keep the model’s stability and improve its explaining ability and forecasting accuracy. It is proved by examples that this method can not only construct models in the case that high multi-correlation exist between variables, but also filter effectively independent variable which is of little relation to dependent variable, and simplify sample set.
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