基于时序数据挖掘的航班延误预测分析

Forecasting analysis of flight delay based on time-sequence data mining

航班延误一直作为国际国内民航业的一个热点问题。通过对航班延误的相关概念进行简要介绍,建立时间序列预测模型,将数据挖掘中隐马尔可夫模型和指数平滑预测方法应用于航班延误预测分析中。通过与所采集时间点的实际航班延误数对比分析来评估预测模型,得到较为理想的预测结果。该分析为航空公司运行指挥中心提供决策支持和理论依据,对保障航班正常运行有着重要的实际意义。

Flight delay has been a hot issue existing in the civil aviation industries at home and abroad. The related con？cepts of flight delays are introduced briefly. A time？series prediction model was established to apply hidden Markov model （HMM） in data mining and exponential smoothing prediction method into the flight delay prediction analysis. The forecasting model is evaluated through comparative analysis of the actual flight delay quantity. A more satisfactory prediction result was ob？tained. The model provided a decision support for airport operations control center. It has important practical significance to guar？antee the normal take？off and landing of flights.