基于聚类方法的机场航班流量时段特征分析
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摘要
通过对机场各特征时段的繁忙程度加以分析,掌握机场航班运行规律,是优化航班结构,调整资源分配的重要基础。采用改进K-means算法对机场进港、离港和总航班数进行一维聚类分析,得到三组相互独立的时段划分结果。利用MMDBK算法对进离港航班二维数据聚类分析,得出进离港相互关联的时段划分结果。对比结果并分析进离港航班流量运行规律,符合机场实际运行情况。能够有效划分机场航班流量时段,并准确掌握机场运行特征。
It is an important factor in optimizing the airport flight structure and the allocation of manpower and material resources in the airport,through the analysis of the busy times of the various characteristics of the airport,in order to master the characteristics of airport flight operation.First,the improved K-means method is used to analyze the number of arrival flights,the number of departure flights and the total number of flights,which results in three independent time intervals.Then MMDBK algorithm is used to analyze the two-dimensional data clustering of the arrival and departure flights,which results in arrival/departure connective time intervals.By comparing the results,the characteristics of the period of airport operation were obtained,which was in accord with the actual operation.This method can cluster airport flight intervals efficiently,and master the characteristics of the period of airport operation accurately.
It is an important factor in optimizing the airport flight structure and the allocation of manpower and material resources in the airport,through the analysis of the busy times of the various characteristics of the airport,in order to master the characteristics of airport flight operation.First,the improved K-means method is used to analyze the number of arrival flights,the number of departure flights and the total number of flights,which results in three independent time intervals.Then MMDBK algorithm is used to analyze the two-dimensional data clustering of the arrival and departure flights,which results in arrival/departure connective time intervals.By comparing the results,the characteristics of the period of airport operation were obtained,which was in accord with the actual operation.This method can cluster airport flight intervals efficiently,and master the characteristics of the period of airport operation accurately.
引文
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[3] 张强,曹仪华,陈勇.民用机场及附近空域空中交通流量优化[J].飞行力学,2007,25(1):84-88.
[4] 张心哲,关伟.基于聚类分析的城市交通路段划分研究[J].交通运输系统工程与信息,2009,9(3):36-42.
[5] Ceder A.Public- transport Vehicle Scheduling with Multivehicle- type[J].Journal of Transportation Research,2011,19(3):485-497.
[6] 李桃迎.交通领域中的聚类分析方法研究[M].北京:科学出版社,2014:165-200.
[7] 王春娥.基于C均值聚类算法的交通时段划分方法研[J].盐城工学院学报,2009,22(4):73-76.
[8] 沈吟东.张仝辉,徐甲.基于K- means聚类算法的公交运营时段分析[J].交通运输系统工程与信息,2014,14(2):87-93.