首页|Classification of aviation incident causes using LGBM with improved cross-validation

Classification of aviation incident causes using LGBM with improved cross-validation

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Aviation accidents are currently one of the leading causes of significant injuries and deaths worldwide.This entices researchers to investigate aircraft safety using data analysis approaches based on an advanced machine learning algorithm.To assess aviation safety and identify the causes of incidents,a classification model with light gradient boosting machine(LGBM)based on the aviation safety reporting system(ASRS)has been developed.It is improved by k-fold cross-validation with hybrid sampling model(HSCV),which may boost classification perfor-mance and maintain data balance.The results show that emp-loying the LGBM-HSCV model can significantly improve accu-racy while alleviating data imbalance.Vertical comparison with other cross-validation(CV)methods and lateral comparison with different fold times comprise the comparative approach.Aside from the comparison,two further CV approaches based on the improved method in this study are discussed:one with a different sampling and folding order,and the other with more CV.Accord-ing to the assessment indices with different methods,the LGBM-HSCV model proposed here is effective at detecting incident causes.The improved model for imbalanced data categorization proposed may serve as a point of reference for similar data pro-cessing,and the model's accurate identification of civil aviation incident causes can assist to improve civil aviation safety.

aviation safetyimbalance datalight gradient boost-ing machine(LGBM)cross-validation(CV)

NI Xiaomei、WANG Huawei、CHEN Lingzi、LIN Ruiguan

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School of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China

School of Aeronautical Engineering,Nanjing Vocational University of Industry Technology,Nanjing 210023,China

National Natural Science Foundation of China Civil Aviation Joint FundResearch on the Dual Prevention Mechanism and Intelligent Management Technology for Civil Aviation Safety Risks

U1833110YK23-03-05

2024

10.23919/JSEE.2024.000035

系统工程与电子技术(英文版)
中国航天科工防御技术研究院 中国宇航学会 中国系统工程学会 中国系统仿真学会

系统工程与电子技术(英文版)

CSTPCD
影响因子：0.64
ISSN：1004-4132
年,卷(期)：2024.35(2)
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