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1 August 2022 Research on automatic classifying method for incident reports with runway incursion
Qizhen Hou, Luoping Wang, Tianyi Yuan
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Proceedings Volume 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022); 122573T (2022) https://doi.org/10.1117/12.2640188
Event: 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 2022, Guangzhou, China
Abstract
The incident report is a common approach used by the international ATC industry for safety management. The report analysis may lead to inconsistent results or missing risk items due to subjective judgements of human. Based on identification of hazards, this paper proposed an automatic method for classifying incident reports by using natural language processing from a safety risk management perspective. The Runway Incursion(RI) reported events were retrieved. Firstly, the hazards related to RI were identified, and report text was calibrated. Then, the similar text was generated to enhance the text data. After that, the words of text were vectored. Finally, the incident reports text classification model was trained. The results show that this method can automatically classify RI reported events according to the categories of hazards.
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Qizhen Hou, Luoping Wang, and Tianyi Yuan "Research on automatic classifying method for incident reports with runway incursion", Proc. SPIE 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 122573T (1 August 2022); https://doi.org/10.1117/12.2640188
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KEYWORDS
Data modeling
Performance modeling
Control systems
Safety
Classification systems
Hazard analysis
Machine learning
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