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空难事故预测是航空安全评价和决策的基础.灰色预测适合于时间短、数据量少和波动不大的系统对象,而马尔可夫链理论适用于预测随机波动大的动态过程.结合灰色预测和马尔可夫链理论的优点,提出了一种灰色马尔可夫SCGM(1,1)C模型.用单因子系统云灰色SCGM(1,1)C模型拟合系统的发展变化趋势,并以此为基础进行了马尔可夫预测.对1979~2003年全球空难人数进行了预测分析,结果表明该模型既能揭示了空难人数变化的总体趋势,又能克服了随机波动性数据对预测精度的影响,具有较强的工程实用性.
Air crash prediction is the basis of aviation safety evaluation and decision-making.Grey prediction is suitable for system objects with short time, little data and little fluctuation, while Markov chain theory is suitable for predicting the dynamic process with large random fluctuations.Combined with gray prediction and Markov chain theory, this paper proposes a gray Markov SCGM (1,1) C model, and uses the one-factor cloud-gray SCGM (1,1) C model to fit the trend of system development. Based on the Markov forecast.A global forecast of the number of air-raids from 1979 to 2003 shows that the model can not only reveal the overall trend of the number of the crash but also overcome the influence of the random fluctuation data on the prediction accuracy , With strong engineering practicability.