This paper presents application of Rough Sets algorithms to prediction of component failures in aerospace domain. To achieve this we first introduce a data preprocessing approach that consists of case selection, data labeling and attribute reduction. We also introduce a weight function to represent the importance of predictions as a function of time before the actual failure. We then build several models using rough set algorithms and reduce these models through a postprocessing phase. End results for failure prediction of a specific aircraft component are presented.
CITATION STYLE
Peña, J. M., Létourneau, S., & Famili, F. (1999). Application of rough sets algorithms to prediction of aircraft component failure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1642, pp. 473–484). Springer Verlag. https://doi.org/10.1007/3-540-48412-4_40
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