摘要
近些年来,大面积航班延误问题已经成为空中交通流量管理部门的难题之一。为了从宏观上描述发生大面积航班延误时的交通状态,提出了空中交通网络流系统的拥堵定义,并对其拥堵程度进行识别和划分。首先从空中交通网络流系统的要素航线和机场的航班运行角度出发,建立了拥堵识别指标体系。其次,根据历史统计数据和熵值法计算权值,并基于模糊综合评价法建立了拥堵程度识别模型。最后,结合实例验证,表明该模型能真实的反映空中交通网络流系统的拥堵状况。
In recent years,the problem of large-scale flight delays has become one of the problems in the civil aviation industry.In order to grasp the traffic state when large-scale flight delay occurs,the definition of congestion in the air traffic network flow system is proposed,and the degree of congestion is identified and divided.Firstly,considering the perspective of airports nodes and air routes,congestion identification indicators are established.Secondly,according to the historical statistics,the weights of different nodes and routes are calculated,in addition the entropy method is used to obtain the weight of the congestion identification index,and the congestion degree recognition model is established based on the fuzzy comprehensive evaluation method.Finally,a example verification shows that the model can truly reflect the congestion status of the air traffic network flow system.
作者
张兆宁
张莹莹
ZHANG Zhao-ning;ZHANG Ying-ying(Air Traffic Management College,Civil Aviation University of China,Tianjin 300300,China)
出处
《科学技术与工程》
北大核心
2019年第36期363-368,共6页
Science Technology and Engineering
基金
国家自然科学基金(71701202)
天津市自然科学基金(18JCQNJC04300)资助
关键词
大面积航班延误
空中交通网络流系统
拥堵
熵值法
模糊综合评价
large-scale flights delay
air traffic network flow system
congestion
entropy method fuzzy comprehensive evaluation
