摘要
机场跑道利用率低一直是制约机场运行效率的主要因素之一。为找出机场跑道利用率低的机场,首先运用数据挖掘的方式,结合国内外相关研究,找到一套适合机场跑道利用率的评价指标体系,利用主成分聚类分析方法,建立基于主成分聚类分析下机场跑道聚类结果;其次对聚类分析得到的相关图表加以说明,并揭示各大机场跑道利用状况的发展趋势并加以分析。结果表明:PCA聚类分析优于聚类分析,具有一定实用性。
Low utilization of the airport runway has been one of the main factors restricting the operational efficiency of the airport. In order to find out the low utilization rate of airport runway,Firstly,the paper u-ses the way of data mining and the related research at country and abroad to find a set of evaluation index system suitable for the utilization rate of airport runway. Based on the principal component clustering anal-ysis method,The clustering results of the airport runway are analyzed. Secondly, the relevant chart ob-tained from the cluster analysis is explained and the development trend of the utilization situation of the major airport runways is revealed and analyzed. The result shows that PCA cluster analysis is superior than cluster analysis and has certain practicability.
出处
《航空计算技术》
2017年第4期62-66,共5页
Aeronautical Computing Technique
基金
国家自然科学基金项目资助(U1533112)
关键词
机场跑道
利用率
数据挖掘
PCA
聚类分析
airport runway
utilization rate
data mining
PCA
cluster analysis
