Abstract
The aim of this chapter is to evaluate a potential of suitable data mining methods for analyses of aviation historical data. In our case, we used public aviation dataset from Federal Aviation Administration (FAA) Accident/Incident Data System containing information about civil aviation accidents or incidents within United States of America. This dataset represents interesting source of data for analytical purposes, e.g. it is possible to evaluate an influence of various factors on both types of events and based on identified hidden relations to generate a prediction model for specified target attribute. We compared our approach with some other existing works in this domain and obtained results are plausible and inspiring. Generated models could be used as a basis for aviation warning system or as a supporting method for different processes related to the aviation industry.
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Babič, F., Lukáčová, A., Paralič, J. (2015). Descriptive and Predictive Analyses of Data Representing Aviation Accidents. In: Zgrzywa, A., Choroś, K., Siemiński, A. (eds) New Research in Multimedia and Internet Systems. Advances in Intelligent Systems and Computing, vol 314. Springer, Cham. https://doi.org/10.1007/978-3-319-10383-9_17
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DOI: https://doi.org/10.1007/978-3-319-10383-9_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10382-2
Online ISBN: 978-3-319-10383-9
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