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Big Data in the Aerospace Industry

Author

Listed:
  • Victor Emmanuell BADEA
  • Alin ZAMFIROIU
  • Radu BONCEA

Abstract

This paper presents the approaches related to the need for large volume data analysis, Big Data, and also the information that the beneficiaries of this analysis can interpret. Aerospace companies understand better the challenges of Big Data than the rest of the industries. Also, in this paper we describe a novel analytical system that enables query processing and predictive analytics over streams of large aviation data.

Suggested Citation

  • Victor Emmanuell BADEA & Alin ZAMFIROIU & Radu BONCEA, 2018. "Big Data in the Aerospace Industry," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 22(1), pages 17-24.
    • Handle: RePEc:aes:infoec:v:22:y:2018:i:1:p:17-24
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    Cited by:

    1. Mitici, Mihaela & de Pater, Ingeborg & Barros, Anne & Zeng, Zhiguo, 2023. "Dynamic predictive maintenance for multiple components using data-driven probabilistic RUL prognostics: The case of turbofan engines," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    2. Lee, Juseong & Mitici, Mihaela, 2023. "Deep reinforcement learning for predictive aircraft maintenance using probabilistic Remaining-Useful-Life prognostics," Reliability Engineering and System Safety, Elsevier, vol. 230(C).

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