Sequential association rules for forecasting failure patterns of aircrafts in Korean airforce

Expert Systems with Applications

Volumn 36, Issue 2 PART 1, 2009, Pages 1129-1133

  Han, Hong Kyu ^a   Kim, Hong Sik ^a   Sohn, So Young ^a  

^a Yonsei University   (South Korea)

Author keywords

Aircraft failure pattern; Sequential association rules

Indexed keywords

AIRCRAFT; ASSOCIATION RULES; FORECASTING; OUTAGES;

AIRCRAFT FAILURE PATTERN; FAILURE PATTERNS; FAILURE SEQUENCES; MAINTENANCE DATABASE; MAINTENANCE SYSTEMS; REPUBLIC OF KOREA AIR FORCES; SEQUENTIAL ASSOCIATION RULES; SEQUENTIAL FAILURES;

AIRCRAFT MANUFACTURE;

EID: 56349156309     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.10.012     Document Type: Article

References (20)

1. Agrawal R., Imielinski T., and Swami A. Database mining: A performance perspective. IEEE Transactions on Knowledge and Data Engineering 6 (1993) 914-925
2. Agrawal, R. & Srikant, R. (1995). Mining sequential patterns. In Proceedings of the 11th international conference on data engineering (pp. 3-14).
3. Bayam E., Liebowitz J., and Agresti W. Older drivers and accidents: A meta analysis and data mining application on traffic accident data. Expert Systems with Applications 29 (2005) 598-629
4. Berry M.J.A., and Linoff G. Data mining techniques. (pp. 243-285) (1997), John Wiley & Sons
5. Carter T.J. Common failures in gas turbine blades. Engineering Failure Analysis 12 (2005) 237-247
6. Dang, B. K. (2003). A study on the inspection and exchange cycle of aircraft. MS thesis, ROKAF University, Seoul, Korea.
7. Delen D., Walker G., and Kadam A. Predicting breast cancer survivability: A comparison of three data mining methods. Artificial Intelligence in Medicine 34 (2005) 113-127
8. Enke D., and Thawornwong S. The use of data mining and neural networks for forecasting stock market returns. Expert Systems with Applications 29 (2005) 927-940
9. Han J., and Camber M. Data Mining: Concepts and Techniques (2001), Morgan Kaufmann Publishers
10. Kusiak A., Dixon B., and Shah S. Predicting survival time for kidney dialysis patients: A data mining approach. Computers in Biology and Medicine 35 (2005) 311-327
11. Lee H.C., Hwang Y.H., and Kim T.G. Failure analysis of nose landing gear assembly. Engineering Failure Analysis 10 (2003) 77-84
12. Létourneau S., Famili F., and Matwin S. Data mining to prediction of aircraft component replacement. IEEE Intelligent Systems & Their Applications 14 (1999) 59-66
13. Lin M.Y., and Lee S.Y. Incremental update on sequential patterns in large databases by implicit merging and efficient counting. Information Systems 29 (2004) 385-404
14. Logistics Command of ROKAF. (2004). Maintenance plan of aircraft.
15. Ossa E.A. Failure analysis of a civil aircraft landing gear. Engineering Failure Analysis 13 (2006) 1177-1183
16. Park J.S., Chen M.S., and Yu P.S. Using a hash-based method with transaction trimming for mining association rules. IEEE Transactions on Knowledge and Data Engineering 9 (1997) 813-825
17. Su F., Zhou C., Lyne V., Du Y., and Shi W. A data-mining approach to determine the spatio-temporal relationship between environmental factors and fish distribution. Ecological Modelling 174 (2004) 421-431
18. Tan C.M., Ang K.M., Tay L.H., and Meng T.Y. Investigation of weight-on-wheel switch failure in F-16 aircraft. Engineering Failure Analysis 12 (2005) 508-519
19. Wu X.R., Li B., Lu F., Tao C.H., Zhang W.F., and Xi N.S. Analysis and control of corrosion cracking in airframe structures. Engineering Failure Analysis 13 (2006) 398-408
20. Yavaş G., Katsaros D., Ulusoy O., and Manolopoulos Y. A data mining approach for location prediction in mobile environments. Data & Knowledge Engineering 54 (2005) 121-146