Study on dynamic evolution characteristics of Wuhan metro network based on complex network
Abstract
With the rapid development of the city, urban metro network is growing rapidly, and the corresponding topology and the importance of stations are changing dynamically. It is of great significance to investigate the node importance and dynamic evolution of urban metro networks for scientific advice on urban metro construction, planning, and operation. In this paper, a new node importance algorithm RNEL (Node importance algorithm based on ReLU function considering Neighborhood force, Entropy and Local link similarity (LLS)) is proposed based on node force, entropy, and topology, and simulation experiments are carried out on the relevant datasets. In addition, the topology of Wuhan metro network from 2004 to 2022 is constructed using Space L, and the network topology parameters of 8 periods are analyzed, and the importance of stations is compared horizontally and vertically. The experimental results show that the proposed RNEL algorithm is superior to the nine node importance algorithms on four evaluation metrics for nine publicly available datasets and four artificial network models. With the spatiotemporal evolution of the Wuhan metro network, nodes become more and more dense, the network tends to be matched, the average distance between stations becomes longer and longer, and the importance of the different types of stations is changing over time. In addition, the importance of the Wuhan metro stations gradually spread from L-1 to L-3 northwest and L-5 southeast. The importance of a stations changes dynamically over time, driven by changes in the type of station, the stations connected to it, and the network environment. This study provides scientific suggestions and aids decision-making for the construction location, station setting and line extension direction of new lines in Wuhan Metro network.
- Publication:
-
Physica A Statistical Mechanics and its Applications
- Pub Date:
- August 2024
- DOI:
- 10.1016/j.physa.2024.129945
- Bibcode:
- 2024PhyA..64829945H
- Keywords:
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- Complex network;
- Node importance;
- Robustness;
- SIR;
- Dynamic evolution;
- Metro network