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航空运行风险的灰色神经网络模型
引用本文:王衍洋,曹义华.航空运行风险的灰色神经网络模型[J].航空动力学报,2010,25(5):1036-1042.
作者姓名:王衍洋  曹义华
作者单位:北京航空航天大学 航空科学与工程学院, 北京 100191
摘    要:采用灰色神经网络的方法,建立了中国民航运行风险的非线性在线模型.模型以风险监测指标作为输入,以评价民航安全的综合指数作为输出,编写了模型计算软件进行仿真计算.计算结果表明,模型预测值与实际安全综合指数值吻合较好,验证了方法的正确性.利用该模型既可以确定风险监测指标中的主要影响指标,为民航降低运行风险提出合理的建议;又可以对民航安全的综合指数进行分析,为行业的安全运行提供预警. 

关 键 词:风险预测    航空安全    民用航空    灰色系统    神经网络
收稿时间:2/9/2010 12:00:00 AM
修稿时间:2010/3/30 0:00:00

Gray neural network model of aviation safety risk
WANG Yan-yang and CAO Yi-hua.Gray neural network model of aviation safety risk[J].Journal of Aerospace Power,2010,25(5):1036-1042.
Authors:WANG Yan-yang and CAO Yi-hua
Institution:School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
Abstract:A non-linear online model of China civil aviation risk was developed by using gray neural network method. Risk model inputs are represented by risk monitoring indicators about China civil aviation safety and output is represented by composite safety index of assessing China civil aviation industry safety. Numerical computation software was programmed based on this model. The agreement of the perception data of computation software with the actual data of composite safety index indicates that,using gray neural network method is correct. Using this risk model,the main influential factors from numerous risk monitoring indicators about civil aviation safety can be found out,and the reasonable proposal can be made for reducing China civil aviation safety risk. On the other hand,analysis of composite safety index of assessing China civil aviation industry safety can be made for providing a warning about China civil aviation safety.
Keywords:risk perception  aviation safety  civil aviation  grey system  neural network
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