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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。
The low utilization rate of airport runways has been one of the main factors restricting the operational efficiency of airports. In order to find out the airport with low utilization rate of airport runway, firstly using data mining method, combined with relevant research at home and abroad, find a set of evaluation index system suitable for the utilization rate of airport runway. By principal component clustering analysis method, Class analysis of the airport runway clustering results; secondly, the cluster analysis of the relevant charts to illustrate and reveal the use of major airport runway trends and analysis. The results show that PCA cluster analysis is superior to cluster analysis and has some practicality.