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Identification of flight accidents causative factors base on SHELLO and improved entropy gray correlation method
In order to effectively identify the key causative factors of civil aviation flight accidents, and establish a forward-looking effective prevention mechanism for flight accidents. Firstly, Corrected SHELLO model is established to classify the causes of civil aviation accidents in China (2015–2019) b...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947263/ https://www.ncbi.nlm.nih.gov/pubmed/36846653 http://dx.doi.org/10.1016/j.heliyon.2023.e13534 |
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author | Chen, Nongtian Sun, Youchao Wang, Zongpeng Peng, Chong |
author_facet | Chen, Nongtian Sun, Youchao Wang, Zongpeng Peng, Chong |
author_sort | Chen, Nongtian |
collection | PubMed |
description | In order to effectively identify the key causative factors of civil aviation flight accidents, and establish a forward-looking effective prevention mechanism for flight accidents. Firstly, Corrected SHELLO model is established to classify the causes of civil aviation accidents in China (2015–2019) based on the integration of SHELL analysis model and Reason organization system concept. Secondly, in view of the randomness and uncertainty gray characteristics of the flight accidents inducing factors, the improved entropy gray correlation algorithm is established for the purpose of importance recognition, which combined with the characteristics of the data sample of inducement classification. Finally, the improved entropy gray correlation algorithm is used to identify and rank the key causative factors of flight accidents. The results showed that the flight accidents crucial causative factor is the human factors which we should pay more attention including the pilot perceptual errors, skill-based errors, decision errors and violation main factors, environmental and organizational factors also play an important role in inducing flight accidents, including complex terrain for approach landing and poor safety management mechanism factors. The method has great practical significance for identifying critical causative factors of flight accidents and improving flight safety. |
format | Online Article Text |
id | pubmed-9947263 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99472632023-02-24 Identification of flight accidents causative factors base on SHELLO and improved entropy gray correlation method Chen, Nongtian Sun, Youchao Wang, Zongpeng Peng, Chong Heliyon Review Article In order to effectively identify the key causative factors of civil aviation flight accidents, and establish a forward-looking effective prevention mechanism for flight accidents. Firstly, Corrected SHELLO model is established to classify the causes of civil aviation accidents in China (2015–2019) based on the integration of SHELL analysis model and Reason organization system concept. Secondly, in view of the randomness and uncertainty gray characteristics of the flight accidents inducing factors, the improved entropy gray correlation algorithm is established for the purpose of importance recognition, which combined with the characteristics of the data sample of inducement classification. Finally, the improved entropy gray correlation algorithm is used to identify and rank the key causative factors of flight accidents. The results showed that the flight accidents crucial causative factor is the human factors which we should pay more attention including the pilot perceptual errors, skill-based errors, decision errors and violation main factors, environmental and organizational factors also play an important role in inducing flight accidents, including complex terrain for approach landing and poor safety management mechanism factors. The method has great practical significance for identifying critical causative factors of flight accidents and improving flight safety. Elsevier 2023-02-05 /pmc/articles/PMC9947263/ /pubmed/36846653 http://dx.doi.org/10.1016/j.heliyon.2023.e13534 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Article Chen, Nongtian Sun, Youchao Wang, Zongpeng Peng, Chong Identification of flight accidents causative factors base on SHELLO and improved entropy gray correlation method |
title | Identification of flight accidents causative factors base on SHELLO and improved entropy gray correlation method |
title_full | Identification of flight accidents causative factors base on SHELLO and improved entropy gray correlation method |
title_fullStr | Identification of flight accidents causative factors base on SHELLO and improved entropy gray correlation method |
title_full_unstemmed | Identification of flight accidents causative factors base on SHELLO and improved entropy gray correlation method |
title_short | Identification of flight accidents causative factors base on SHELLO and improved entropy gray correlation method |
title_sort | identification of flight accidents causative factors base on shello and improved entropy gray correlation method |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9947263/ https://www.ncbi.nlm.nih.gov/pubmed/36846653 http://dx.doi.org/10.1016/j.heliyon.2023.e13534 |
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