Machine learning for helicopter accident analysis using supervised classification: Inference, prediction, and implications

Zhaoyi Xu, Joseph Homer Saleh and Rachmat Subagia

Reliability Engineering and System Safety, 2020, vol. 204, issue C

Abstract: The work is part of a larger effort whose end-objective is to contribute toward a better understanding of helicopter accidents and improving their safety track record. Herein, we extend the domain of application of Machine Learning (ML) to a new topic, namely helicopter accidents. Our objectives are twofold: (1) to benchmark the performance of different classifiers in examining our dataset, and (2) to leverage the best-in-class classifier to identify novel insights for improving helicopter accident analysis and prevention.

Keywords: Machine learning; Classifier; Deep neural network; Helicopter accident; Safety (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:204:y:2020:i:c:s0951832020307110

DOI: 10.1016/j.ress.2020.107210

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