Combining apriori algorithm and constraint-based genetic algorithm for tree induction for aircraft electronic ballasts troubleshooting

Authors:
Chaochang Chiu;Pei-Lun Hsu;Nan-Hsing Chiu
Affiliations:
Department of Information Management, Yuan Ze University, Taiwan, R.O.C.;Department of Electronic Engineering, Ching Yun University, Taiwan, R.O.C.;Department of Information Management, Yuan Ze University, Taiwan, R.O.C.
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Year:
2006

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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.