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Analysing Flight Data Using Clustering Methods

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5177))

Abstract

This paper reviews existing forms of density-based, partitional and hierarchical clustering methods in the context of flight data analysis. Advantages and disadvantages are fully explored with a focus on proposing a clustering-based ensemble framework for monitoring flight data in order to search for anomalies during flight operation. Case studies in selected flight scenarios are provided to demonstrate the potential of clustering methods and their integration with reasoning techniques in detecting abnormal flights.

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Ignac Lovrek Robert J. Howlett Lakhmi C. Jain

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© 2008 Springer-Verlag Berlin Heidelberg

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Jesse, C., Liu, H., Smart, E., Brown, D. (2008). Analysing Flight Data Using Clustering Methods. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85563-7_92

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  • DOI: https://doi.org/10.1007/978-3-540-85563-7_92

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85562-0

  • Online ISBN: 978-3-540-85563-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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