A measure of identifying influential waypoints in air route networks.

A measure of identifying influential waypoints in air route networks.
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识别航线网络中有影响力的航路点的方法

DOI:
10.1371/journal.pone.0203388
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发表时间:
2018
期刊:
影响因子:
3.7
通讯作者:
Lu C
Lu C
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Ren G;Zhu J;Lu C

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航线网络作为空中航班运行的基本载体,对航班的平稳运行具有重要意义。然而,航路点是航路的核心部分,因此,识别有影响的航路点是ARN中的一个重要课题。本文提出了一种基于改进的熵权(IEW)法的ARN节点影响力识别方法。然后,将度、贴近度、介数和特征向量作为ARN的多属性在IEW中的应用。采用IEW方法对多属性进行聚合,得到各航路点影响的评价。为了验证IEW方法的有效性,我们选取了三个真实的ARN,在SIR模型下进行了实验。结果表明了该方法的有效性和实用性。
As the basic carrier of air flight operation, air route network (ARN) is of great significance to the smooth operation of flights. However, the waypoint is a core part of the route, so it is an important topic to identify influential waypoints in ARN. In this paper, a method to identify the influence of the node in ARN based on an improved entropy weight (IEW) method is proposed. Then, centrality measures including degree, closeness, betweenness and eigenvector as the multi-attribute of ARN in IEW application. IEW method is used to aggregate the multi-attribute to obtain the evaluation of the influence of each waypoint. To demonstrate the effectiveness of the IEW method, three real ARNs are selected to conduct several experiments with susceptible infected recovered (SIR) model. The results show the efficiency and practicability of the proposed method.
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