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所属单位：Nanjing University of Aeronautics and Astronautics, College of Economics and Management

发表刊物：Expert Systems With Application

关键字：Commercial Aviation Safety; Near Miss; GM (1, 1); BP Neural Network; Grey Neural Network

摘要：Owing to unprecedented level of safety management, there have been few commercial aviation accidents recently, obstructing accurate prediction of safety trends. The innovative approach of proactive safety management was employed to replace reactive safety management for predicting commercial aviation near misses. In light of positive correlation between flight time and commercial aviation near-miss with different severity levels, this study aims to predict total / serious / non-serious near-miss per million flight hours. Considering grey system theory is good at prediction without adequate data, and artificial neural networks can handle nonlinear data well, the combined models of grey neural networks were developed for forecasting three data sequences over time respectively. Based on the empirical results of commercial aviation near-miss forecasting, BP neural network had the potential to enhance accuracy of grey prediction model. The three statistical measures of MAE/MSE/MAPE denoted the combined model of grey neural network outperformed the single model of GM (1, 1) or BP neural network. Predictions with a high degree of accuracy is beneficial to determining actual trends of commercial aviation near-misses at present or in future. Quantitative data will be offered for making specific decisions on maintaining preventive measures or promoting commercial aviation safety performance by introducing additional management actions.

论文类型：期刊论文

学科门类：管理学

文献类型：J

是否译文：否

发表时间：2024-07-18

收录刊物：SCI

通讯作者：Xingnan Zhou,Haonan Qi,Nan Li,Chuanmin Mi