Abstract
Air route network (ARN) is one of the most important transportation networks and the key waypoints (nodes) have significant influence on the stability and robustness of the ARN. In this paper, a network agglomeration relative entropy centrality (NAREC) method to identify influential nodes in ARNs is proposed, based on the network agglomeration and relative entropy theory. The basic topological features of the regional ARNs in Beijing, Shanghai and Guangzhou are analyzed and then the proposed method is applied to identifying influential nodes in the three networks. At last, the effectiveness of the NAREC method is demonstrated by the susceptible-infected-removed (SIR) model and the Kendall's tau coefficient. Results show that the proposed method is applicable and effective.
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