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Semantic Scholar · Article (Expert systems with applications)

Natural Language Processing for the identification of Human factors in aviation accidents causes: An application to the SHEL methodology

Published 2021-12-30 From Expert systems with applications 4 authors
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Attribution

This is the abstract and citation. Full text lives at Semantic Scholar — we link out rather than host. All credit to the authors and Expert systems with applications.

Abstract

Verbatim from Semantic Scholar. Not paraphrased, not summarized.

This paper considers the issue of machine learning techniques by leveraging on the state-of-the-art technologies of Natural Language Processing, adapted to the Software Hardware Environment Liveware standard accident causality model and tested on a set of real accidents.

Authors

  • G. Perboli
  • M. Gajetti
  • S. Fedorov
  • Simona Lo Giudice

Keywords

  • Computer Science
  • Engineering

Citation: G. Perboli, M. Gajetti, S. Fedorov , et al. (2021). Natural Language Processing for the identification of Human factors in aviation accidents causes: An application to the SHEL methodology. Expert systems with applications. Semantic Scholar ID 83c4acba9c532df287e40ef1284146363f1f14be. https://doi.org/10.1016/J.ESWA.2021.115694 ↗