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Discrete Dynamics in Nature and Society
Volume 2012 (2012), Article ID 291965, 12 pages
http://dx.doi.org/10.1155/2012/291965
Research Article

Evolving Model for the Complex Traffic and Transportation Network Considering Self-Growth Situation

School of Management, Xiamen University, Xiamen 361005, China

Received 4 May 2012; Revised 29 June 2012; Accepted 13 July 2012

Academic Editor: Wuhong Wang

Copyright © 2012 Wei Zhang and Di Xu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

It has been approved that the scale-free feature exists in various complex networks, such as the internet, the cell or the biological networks. In order to analyze the influence of the self-growth phenomenon during the growth on the structure of traffic and transportation network, we formulated an evolving model. Based on the evolving model, we prove in mathematics that, even that the self-growth situation happened, the traffic and transportation network owns the scale-free feature due to that the node degree follows a power-law distribution. A real traffic and transportation network, China domestic airline network is tested to consolidate our conclusions. We find that the airline network has a node degree distribution equivalent to the power-law of which the estimated scaling parameter is about 3.0. Moreover the standard error of the estimated scaling parameter changes according to the self-growth probability. Our findings could provide useful information for determining the optimal structure or status of the traffic and transportation network.