Abstract
Reliable and effective maintenance support is vital to the airline operations and flight safety. This research proposes the hybrid of apriori algorithm and constraint-based genetic algorithm (ACBGA) approach to discover a classification tree for electronic ballasts troubleshooting. Compared with a simple GA (SGA) and the Apriori algorithms with GA (AGA), the ACBGA achieves higher classification accuracy for electronic ballast data.
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© 2006 Springer-Verlag Berlin Heidelberg
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Chiu, C., Hsu, PL., Chiu, NH. (2006). Combining Apriori Algorithm and Constraint-Based Genetic Algorithm for Tree Induction for Aircraft Electronic Ballasts Troubleshooting. In: Jiao, L., Wang, L., Gao, Xb., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881070_53
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DOI: https://doi.org/10.1007/11881070_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45901-9
Online ISBN: 978-3-540-45902-6
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