2022 International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM)
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Abstract

The hub nodes in transportation network have great influences on the connectivity, reliability and safety of the entire network. However, most of the currentresearch only consider the structure of transportation network and neglect the traffic-related factors. Thus, present study proposes hub nodes mining algorihm that combines traffic flow feature and Betweenness centrality, the importance of the node is related to the Betweenness of nodes, the traffic flow, and the grade of the connected road. Moreover, it introduced fast algorithm Ulrik Brandes reduce the complexity of calculation. The results of the simulation indicate that the proposed algorithm can mining hub nodes effectively in the road network including bridge nodes. The findings of this paper can be applied to provide decision-making support for the management of transportation network and the optimization of traffic construction
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