Abstract
Flight operations quality assurance (FOQA) can be applied to monitoring and analyzing the data recorded in a flight to improve line operations and safety. In view of the requirements of FOQA and the shortage of general data processing algorithms, clustering analysis and density-based spatial clustering of applications with noise (DBSCAN) algorithm are studied depending on data mining, and FOQA based on clustering analysis is presented. The process of flight data analysis is discussed with this algorithm. The practicability and universality of DBSCAN algorithm is validated by the clustering analysis instance of an abnormal data during takeoff.
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References
Xiaoli L (2002) Human factor accident/incident classification standard and classified statistical report on human factor accident/incident of China Civil Aviation in recent twelve years. J China Saf Sci J 12(5):55–62 (in Chinese)
Lijuan H, Zheng L, Yu W (2011) A concise course book on SPSS statistical analysis. Electronic Industry Press (in Chinese)
Yan C (2011) Application of data mining. Tsinghua University Press, Beijing (in Chinese)
Keyun H, Fengzhan T, Houkuan H (2008) Application of data mining. Tsinghua University Press, Beijing (in Chinese)
Heng Z (2005) Study on some issues of data clustering in data mining. Xi’an Electronic and Engineering University, Xi’an (in Chinese)
Mikawa K, Ishidat T, Goto M (2011) A proposal of extended cosine measure for distance metric learning in text classification. In: IEEE international conference on systems, man, and cybernetics (SMC), pp 1741–1746
Shuhua R, Fan A (2011) K-means clustering algorithm based on coefficient of variation. In: 4th international congress on image and signal processing, pp 2076–2079
Shah GH (2012) An improved DBSCAN, a density based clustering algorithm with parameter selection for high dimensional data sets. In: Proceedings of the 5th international conference on machine learning and cybernetics
Budhi GS, Adipranata R, Sugiarto M (2011) Pengelomopokan Sunspot Pata Citra Digital Mahatari Menggunakan Metode Clustering DBSCAN. In: Seminar Nasional Aplikasi Teknologi Informasi
Vijayalakshmi S, Punithavalli M (2010) Improved varied density based spatial clustering algorithm with noise. In: IEEE international conference on computational intelligence and computing research-ICCIC
Chaojiang H, Lie C, Quanfa Y (2012) Application of FDR system. National Defense Industry Press (in Chinese)
Zhipeng L, Shangjun L, Chunpeng Z (2005) Study of a flight data based expert system. J Aircr Des 2:52–58 (in Chinese)
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© 2014 Springer-Verlag Berlin Heidelberg
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Sun, Z., Ma, C., Li, W., Shen, C. (2014). Flight Operations Quality Assurance Based on Clustering Analysis. In: Wang, J. (eds) Proceedings of the First Symposium on Aviation Maintenance and Management-Volume II. Lecture Notes in Electrical Engineering, vol 297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54233-6_46
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DOI: https://doi.org/10.1007/978-3-642-54233-6_46
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