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航空运行风险的灰色神经网络模型 被引量:11

Gray neural network model of aviation safety risk
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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. 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.
出处 《航空动力学报》 EI CAS CSCD 北大核心 2010年第5期1036-1042,共7页 Journal of Aerospace Power
关键词 风险预测 航空安全 民用航空 灰色系统 神经网络 risk perception aviation safety civil aviation grey system neural network
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参考文献7

  • 1Air Safety Week. Single index proposed to measure safety of aviation system .[EB/OL], Pace Publications, 2008 [2010-01-25]. http://findarticles, com/p/articles/mi_m0UBT/ is_35_17/ai_107767512.
  • 2李敬,陈艳秋,何珮.中国民航业安全风险监测与仿真研究[J].中国安全科学学报,2009,19(7):20-25. 被引量:13
  • 3LI Jing,WANG Yanyang. The safety indices of China civil aviation industry[C]ffFSF 60th Annual International Air Safety Seminar. Seoul, Korea: Flight Safety Foundation, 2007:1-15.
  • 4史忠科.神经网络控制理论[M].西安:西北工业大学出版社,2000..
  • 5Hartrnan E J, Keeler J D, Kowalski J M. Layered neural networks with Gaussian hidden units as universal approximations[J]. Neural Computation, 1990(2): 210-215.
  • 6Kung S Y. Digital neural networks[M], New Jersey:Prentice-Hall Inc. ,1993.,175 179.
  • 7吕宏辉,钟珞,夏红霞.灰色系统与神经网络融合技术探索[J].微机发展,2000,10(3):3-5. 被引量:25

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