Data-driven mid-air collision risk modelling using extreme-value theory
- DOI
- 10.1016/j.ast.2023.108646
- Published
- 2023-09-25
- Container
- Aerospace Science and Technology
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1016/j.ast.2023.108646,
title = {Data-driven mid-air collision risk modelling using extreme-value theory},
author = {Benoit Figuet and Raphael Monstein and Manuel Waltert and Jérôme Morio},
year = {2023},
journal = {Aerospace Science and Technology},
doi = {10.1016/j.ast.2023.108646},
url = {https://doi.org/10.1016/j.ast.2023.108646}
}RIS
TY - JOUR TI - Data-driven mid-air collision risk modelling using extreme-value theory AU - Benoit Figuet AU - Raphael Monstein AU - Manuel Waltert AU - Jérôme Morio PY - 2023 JO - Aerospace Science and Technology DO - 10.1016/j.ast.2023.108646 UR - https://doi.org/10.1016/j.ast.2023.108646 ER -
APA
Figuet, B., Monstein, R., Waltert, M., & Morio, J. (2023). Data-driven mid-air collision risk modelling using extreme-value theory. Aerospace Science and Technology. https://doi.org/10.1016/j.ast.2023.108646
Source records
- hal · retrieved 2026-11-10T11:34:42.526Z