The invention relates to the field of airport scene traffic situation assessment, in particular to an airport scene road section traffic situation assessment method and device based on k-means clustering. According to the airport scene road section traffic situation assessment method based on k-means clustering, when the traffic situation of a scene road section is assessed, the important influence of interaction and change trend of multiple factors on the operation condition of an airport is considered; dimensionality reduction is carried out on indexes through a principal component analysis method, key information is effectively extracted, data dimensionality is reduced, and a basis is provided for subsequent clustering analysis; by analyzing the clustering result, it is found that the clustering result can reflect the change of situation levels of different types of road sections to a certain extent; therefore, the method can be used for optimizing the operation efficiency and safety of the airport.
本发明涉及机场场面交通态势评估领域,具体涉及一种基于k‑means聚类的机场场面路段交通态势评估方法及装置。本发明的基于k‑means聚类的机场场面路段交通态势评估方法在评估场面路段的交通态势时,考虑了多个因素的相互作用和变化趋势对机场的运行情况产生重要影响;通过主成分分析法将指标降维,有效地提取了关键信息,减少了数据维度,为后续的聚类分析提供了基础;通过对聚类结果进行分析,发现聚类结果能在一定程度上反映不同类型路段的态势等级的变化;从而可以用于优化机场的运行效率和安全性。
Airport scene road section traffic situation assessment method and device based on k-means clustering
基于k-means聚类的机场场面路段交通态势评估方法及装置
2024-02-02
Patent
Electronic Resource
Chinese
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