基于标准欧氏距离的燃油流量缺失数据填补算法

摘要

To reduce the negative impact of aircraft fuel consumption statistical inference accuracy caused by the data missing,an estimated method based on standardized Euclidean distance was proposed to solve the fuel flow data missing problems.The nearest neighbors were chosen by the standardized Euclidean distance between QAR data samples,and then entropy was utilized to obtain the weight of the nearest neighbors.The missing value was estimated by the weighted average fuel flow of the nearest neighbors.Experiments prove that this method is valid to process fuel consumption data missing problems,and its performance is higher than the other imputation methods based on normal Euclidean distance,Mahalanobis distance or reduced relational grade.%为减小数据缺失对飞机油耗统计推断精度带来的负面影响,针对基于传统欧氏距离、马氏距离以及精简关联度的最近邻填补算法的不足,提出了一种基于标准欧氏距离的填补算法来估计QAR(Quick Access Recorder)数据中部分燃油流量数值的缺失.该算法通过QAR数据样本之间的标准欧氏距离选择最近邻样本,并利用熵值赋权法计算最近邻的加权系数,基于最近邻样本中燃油流量的加权平均即可得到缺失燃油流量的估计值.实验结果表明,标准欧氏距离能够有效度量样本相似性,所提出的算法优于常规填补算法,是处理飞机油耗数据缺失的一种有效方法.