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基于易感者-染病者-易感者的时变机场网络延误传播模型
引用本文:王兴隆,朱丽纳,张淑婷.基于易感者-染病者-易感者的时变机场网络延误传播模型[J].科学技术与工程,2019,19(34):414-419.
作者姓名:王兴隆  朱丽纳  张淑婷
作者单位:中国民航大学空中交通管理学院,天津300300;中国电子科技集团公司第二十八研究所 空中交通管理系统与技术国家重点实验室,南京210014;中国民航大学空中交通管理学院,天津300300;中国民用航空华北地区空中交通管理局,北京100621
基金项目:国家自然科学基金资助(61571441);国家重点研发计划项目(2016YFB0502405);空中交通管理系统与技术国家重点实验室开放基金项目资助(SKLATM201705);中央高校基本科研业务经费专项资金项目(3122014D036)
摘    要:为宏观角度分析机场网络延误传播机理,基于复杂网络易感者-染病者-易感者(susceptible-infective-susceptible, SIS)传染病模型建立了延误传播模型。从机场网络延误传播的时变性和与SIS传染病模型的相似性入手,以机场为节点,定义了其在机场网络延误传播过程里存在的不同状态,依据节点状态间的转变机理,建立机场网络延误传播动力学模型,并根据航班时刻规划航班流运输路径。以全国153个机场为例,采集航班延误数据,进行模型仿真并分析实验参数。结果表明:机场网络延误节点的延误影响范围有限,且网络对延误的传播能力具有一定的抑制性,很少出现全网的崩溃现象;该模型具有有效性和实用性,可以较好地仿真实际延误的传播过程。

关 键 词:航空运输  空中延误  易感者-染病者-易感者模型  机场网络  传播模型  时变网络
收稿时间:2019/5/7 0:00:00
修稿时间:2019/6/26 0:00:00

Time-varying Airport Network delay propagation model based on SIS
WANG Xing-long,ZHU Li-na and ZHANG Shu-ting.Time-varying Airport Network delay propagation model based on SIS[J].Science Technology and Engineering,2019,19(34):414-419.
Authors:WANG Xing-long  ZHU Li-na and ZHANG Shu-ting
Institution:College of Air Traffic Management, Civil Aviation University of China,,
Abstract:In order to analyze the mechanism of airport network delay propagation from a macro perspective. a delay propagation model was established based on the complex network SIS infectious disease model. Starting from the similarity between the time-varying airport network delay propagation and the SIS infectious disease model, the airports are built as nodes to establish a network. Defines the different states of airport nodes in the process of airport network delay propagation. Establishing airport network delay propagation dynamics model based on the transition mechanism between node states. And plan flight flow path based on flight schedule. Taking 153 airports nationwide as an example, collecting flight delay data, performing model simulation and analyzing experimental parameters. The results show that the delay of the delay of the airport network is limited. The network will inhibit the propagation of delays and will not cause the collapse of the entire network. The model is effective and practical, and can simulate the actual delay of the propagation process.
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