by a high-speed rail network

作者: Luo, JJ (Luo, Juanjuan); Fei, T (Fei, Teng); Tian, M (Tian, Meng); Liu, YF (Liu, Yifei); Bian, M (Bian, Meng)

来源出版物: JOURNAL OF GEOGRAPHICAL SYSTEMS DOI: 10.1007/s10109-023-00419-8提前访问日期: JUN 2023

摘要: As a mathematical scaffold for network science, graph theory abstracts complex systems into complex networks. However, graphs ignore the multiplicity of combinatorial relationships in network systems, leading to limitations in graph-based metrics reflecting the importance of nodes. To address the shortcomings of graphs in describing network complexity, this study proposes the use of co-occurrence pattern truth tables to represent the combinations of multiple nodes in a network. Based on this, the concept of positive sensitivity is proposed to measure one aspect of the importance of nodes in a network. In addition, network sensitivity is proposed to depict the robustness of the network. The proposed approach is verified to be workable with Monte Carlo simulations and a real network exemplified by the high-speed rail network, constructed with provincial capitals of China as nodes. The results in comparison with traditional graph theory-based indices show that both the nodes and the network are assessed with reasonable results different from those of the graph-derived metrics. This study focuses on the combinatorial relationships of nodes in networks, providing a new perspective for the analysis of complex networks.

作者关键词: Complex network; Node importance; Network sensitivity; Boolean function; Co-occurrence truth table

地址: [Luo, Juanjuan; Fei, Teng; Liu, Yifei] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Tian, Meng] Yangzhou Univ, Business Sch, Yangzhou 225127, Peoples R China.

[Bian, Meng] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China.

通讯作者地址: Fei, T (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址: feiteng@whu.edu.cn

影响因子：2.9