基于BP神经网络的民用航空航段安全风险评估

Safety risk assessment model for civil aviation flight phase based on BP neural network

摘要:

基于反向传播(BP)神经网络，建立了民用航空航段安全风险评估模型。采用MATLAB软件并通过某航空公司A320机型的实际飞行数据，实现神经网络模型的训练与检测，误差在可接受范围内。试验结果表明，该评估模型能够体现和反映航段安全风险。同时，基于此模型建立了航段安全风险评估原型系统，为航空公司进一步实施安全管理以及民航局履行政府安全监管职能提供科学手段和工具。

Abstract:

This research built a flight phase safety risk assessment model basing on Back Propagation(BP) neural network. By using MATLAB software and flight data of A320，the training and verification of the model were realized，and the errors were acceptable. The results shows that the model is capable of predicting the possible risk in a flight phase. Moreover，the flight phase safety risk assessment system can provide scientific solutions and can be taken as a tool, which facilitates not only the management regarding flight safety for an airline company，but also the role in flight supervision for the civil aviation administration.