Airline Crash Investigation Using Data Mining Techniques

Authors

  • Manasvi Dedania  Department of information Technology Mumbai University Maharashtra, India
  • Ekta Bhosale  Department of information Technology Mumbai University Maharashtra, India
  • Ankit Champaneria  Department of information Technology Mumbai University Maharashtra, India
  • Shubam Lotlikar  Department of information Technology Mumbai University Maharashtra, India
  • Prof. Rovina D`britto  Assistant Professor, Department of information Technology Mumbai University Maharashtra, India

Keywords:

Data Mining, Clustering K-Means Clustering, Cosine Similarity

Abstract

Air transportation systems are designed to ensure that aircraft accidents are rare events. To minimize these accidents, factors causing or contributing to accidents must be understood and prevented. Previous research has studied accident data to determine these factors. In this research work crash investigation and analysis of the flights are done. Airplane crash may be caused due to pilot error, mechanical failure, bad weather, sabotages or human error. In this research we employed a data mining technique to conduct a holistic analysis of aircraft incident data in relation to the accident data. The analysis identifies relationships between the accident and incident data and finds patterns of causal and contributory factors which are significantly associated with aircraft accidents.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Manasvi Dedania, Ekta Bhosale, Ankit Champaneria, Shubam Lotlikar, Prof. Rovina D`britto, " Airline Crash Investigation Using Data Mining Techniques" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.1200-1204, March-April-2018.