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从航班延误链式波及的角度出发,分析了影响航班过站时间的多种因素,建立了贝叶斯网络模型,模型能够清晰地反映多种因素对下游航班过站时间的影响。提出了基于贝叶斯网络参数估计的航班延误预测算法,当航班发生起飞延误时能够预测下游航班的起飞时间和延误状况。对算法进行了实现,并利用实际航班数据进行仿真,结果表明了该算法有比较高的预测准确率。
From the point of view of flight delays, the paper analyzes the various factors that affect flight departure time and builds a Bayesian network model. The model can clearly reflect the influence of many factors on the transit time of downstream flights. A flight delay forecasting algorithm based on Bayesian network parameter estimation is proposed, which can predict the take-off time and the delay status of the downstream flight when the take-off delay occurs. The algorithm is implemented, and the actual flight data is used to simulate. The result shows that this algorithm has higher prediction accuracy.