基于灰色聚类的大面积航班延误的延误程度评估

为准确评估大面积航班延误的延误程度,分析了空中交通网络中大面积航班延误的形成过程,在分析人、机、环、管等影响大面积航班延误程度的因素的基础上,选取能表征大面积航班延误程度的节点、航线、到达关联节点指标.基于空中交通网络流系统建立了大面积航班延误程度评估的指标体系.利用层次分析法和熵理论方法,组合赋权确定各指标权重.建立了评估大面积航班延误程度的灰色综合聚类评估模型.选取2019年某发生大面积航班延误的空域进行航班延误程度评估.算例分析结果表明:运用该模型所评估的发生大面积航班延误的空域的延误程度与实际情况相符.

Estimation of the delay of large-scale flight delay based on grey clustering

In order to accurately estimate the delay of large-scale flight delays, the formation process of large-scale flight delays in air traffic networks is analyzed. Based on the analysis of factors affecting the delay of large-scale flights, such as people, machines, rings and tubes, the characteristics can be characterized. Nodes, routes, and arrival node indicators for large-scale flight delays. Based on the air traffic network flow system, an indicator system for large-scale flight delay assessment was established. Using the analytic hierarchy process and the entropy theory method, the combination weights determine the weights of each indicator. A grey comprehensive clustering evaluation model for assessing the delay of large-scale flight delays was established. The airspace of a large-scale flight delay in 2019 was selected for flight delay assessment. The results of the example analysis show that the degree of delay in the airspace in which large-scale flight delays are estimated using the model is consistent with the actual situation.