Research on Shortest Paths-Based Entropy of Weighted Complex Networks

  • Zundong Zhang
  • Zhaoran Zhang
  • Weixin Ma
  • Huijuan Zhou
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 482)

Abstract

In order to provide a new measure for the structural characteristics of complex networks, a new shortest paths-based entropy (SPE) is proposed to describe the influence of degree and shortest path on network characteristics in this paper . The novel measurement based on shortest paths of node pairs and weights of edges. Many different approaches to measuring the complexity of networks have been developed. Most existing measurements unable to apply in weighted network that consider only one characteristic of complex networks such as degree or betweenness centrality. To some extent, the shortest paths-based entropy overcome the inadequacies of other network entropy descriptors. The method combines node degrees with shortest paths. For the purpose of proving the reasonableness of this method, we carry on a contrast analysis of the SPEs of different type networks, including: ER random network, BA scale-free network, WS small-world network and grid network. The results show that shortest paths-based entropy of complex networks is meaningful to evaluation of networks.

Keywords

Complex networks Contrast analysis Shortest Paths-based entropy (SPE) 

Notes

Acknowledgements

This paper is supported by The Chinese the State 13 Five-year Scientific and Technological Support Project (2016YFB1200402), The Big-Data Based Beijing Road Traffic Congestion Reduction Decision Support Project (PXM2016014212000036) and The Project of The Innovation and Collaboration Capital Center for World Urban Transport Improvement (PXM2016014212000030).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Zundong Zhang
    • 1
  • Zhaoran Zhang
    • 1
  • Weixin Ma
    • 1
  • Huijuan Zhou
    • 1
  1. 1.Beijing Key Lab of Urban Road Transportation Intelligent Control TechnologyNorth China University of TechnologyBeijingPeople’s Republic of China

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