A measure of identifying influential waypoints in air route networks
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所属单位：民航学院
发表刊物：PLOS ONE
关键字：COMPLEX NETWORKS COMMUNITY STRUCTURE CENTRALITY NODES IDENTIFICATION SPREADERS RANKING
摘要：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.
ISSN号：1932-6203
是否译文：否
发表时间：2018-09-18
合写作者：Ren, Guangjian,卢朝阳
通讯作者：Ren, Guangjian,朱金福