中国物理B ›› 2007, Vol. 16 ›› Issue (8): 2304-2309.doi: 10.1088/1009-1963/16/8/024

• GENERAL • 上一篇    下一篇

Detecting and describing the modular structures of weighted networks

李克平, 高自友   

  1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
  • 收稿日期:2006-11-14 修回日期:2006-12-28 出版日期:2007-08-20 发布日期:2007-08-20
  • 基金资助:
    Project supported by the National Basic Research Program of China (Grant No 2006CB705500), the National Natural Science Foundation of China (Grant No 60634010), New Century Excellent Talents in University (Grant No NCET-06-0074) and the Key Project of Chi

Detecting and describing the modular structures of weighted networks

Li Ke-Ping(李克平) and Gao Zi-You(高自友)   

  1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
  • Received:2006-11-14 Revised:2006-12-28 Online:2007-08-20 Published:2007-08-20
  • Supported by:
    Project supported by the National Basic Research Program of China (Grant No 2006CB705500), the National Natural Science Foundation of China (Grant No 60634010), New Century Excellent Talents in University (Grant No NCET-06-0074) and the Key Project of Chi

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摘要： In the functional properties of complex networks, modules play a central role. In this paper, we propose a new method to detect and describe the modular structures of weighted networks. In order to test the proposed method, as an example, we use our method to analyse the structural properties of the Chinese railway network. Here, the stations are regarded as the nodes and the track sections are regarded as the links. Rigorous analysis of the existing data shows that using the proposed algorithm, the nodes of network can be classified naturally. Moreover, there are several core nodes in each module. Remarkably, we introduce the correlation function $G_{rs}$, and use it to distinguish the different modules in weighted networks.

Abstract: In the functional properties of complex networks, modules play a central role. In this paper, we propose a new method to detect and describe the modular structures of weighted networks. In order to test the proposed method, as an example, we use our method to analyse the structural properties of the Chinese railway network. Here, the stations are regarded as the nodes and the track sections are regarded as the links. Rigorous analysis of the existing data shows that using the proposed algorithm, the nodes of network can be classified naturally. Moreover, there are several core nodes in each module. Remarkably, we introduce the correlation function $G_{rs}$, and use it to distinguish the different modules in weighted networks.

Key words: weighted networks, modular structure, railway network

中图分类号:  (Networks and genealogical trees)

  • 89.75.Hc
89.75.Fb (Structures and organization in complex systems)