Computer Science ›› 2017, Vol. 44 ›› Issue (Z6): 109-111.doi: 10.11896/j.issn.1002-137X.2017.6A.023

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Fuel Flow Missing-value Imputation Method Based on Standardized Euclidean Distance

CHEN Jing-jie and CHE Jie   

  • Online:2017-12-01 Published:2018-12-01

Abstract: 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.

Key words: Standardized euclidean distance,Fuel flow missing value estimation,KNN imputation method,Entropy,RKNN

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