Title :
Data mining to predict aircraft component replacement
Author :
Létourneau, Sylvain ; Famili, Fazel ; Matwin, Stan
Author_Institution :
Inst. for Inf. Tech., Nat. Res. Council of Canada, Ottawa, Ont., Canada
Abstract :
Aircraft sensors generate vast amounts of data, much of which languishes in storage after its initial analysis. The authors have developed an approach for using this data to build models for predicting aircraft component failure. Their approach addresses several key data-mining issues
Keywords :
aerospace computing; data mining; aircraft component failure; aircraft component replacement; aircraft sensors; data mining; Aircraft manufacture; Biomedical equipment; Data analysis; Data mining; Labeling; Marine vehicles; Medical services; Predictive models; Sensor phenomena and characterization; Vents;
Journal_Title :
Intelligent Systems and their Applications, IEEE
DOI :
10.1109/5254.809569
