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基于时序数据挖掘的航班延误预测分析
引用本文:罗凤娥,张成伟. 基于时序数据挖掘的航班延误预测分析[J]. 现代电子技术, 2014, 0(24): 52-55
作者姓名:罗凤娥  张成伟
作者单位:中国民用航空飞行学院空中交通管理学院
基金项目:民航局安全能力建设项目(14014J0260004);民航局引导资金项目(2146905)
摘    要: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。

关 键 词:航班延误  数据挖掘  时间序列模型  决策支持

Forecasting analysis of flight delay based on time-sequence data mining
LUO Feng-e;ZHANG Cheng-wei. Forecasting analysis of flight delay based on time-sequence data mining[J]. Modern Electronic Technique, 2014, 0(24): 52-55
Authors:LUO Feng-e  ZHANG Cheng-wei
Affiliation:LUO Feng-e;ZHANG Cheng-wei;College of Air Traffic Management,Civil Aviation Flight University of China;
Abstract: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.
Keywords:flight delay  data mining  time-series model  decision support
本文献已被 CNKI 维普 等数据库收录!
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