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摘要
We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique (maximal complete sub-graph) at each time step. And the cliques in the network overlap with each other. The structural expansion of the weighted clique network is combined with the edges'; weight and vertices'; strengths dynamical evolution. The model is based on a weight-driven dynamics and a weights'; enhancement mechanism combining with the network growth. We study the network properties, which include the distribution of vertices'; strength and the distribution of edges'; weight, and find that both the distributions follow the scale-free distribution. At the same time, we also find that the relationship between strength and degree of a vertex are linear correlation during the growth of the network. On the basis of mean-field theory, we study the weighted network model and prove that both vertices'; strength and edges'; weight of this model follow the scale-free distribution. And we exploit an algorithm to forecast the network dynamics, which can be used to reckon the distributions and the corresponding scaling exponents. Furthermore, we observe that mean-field based theoretic results are consistent with the statistical data of the model, which denotes the theoretical result in this paper is effective.
- 出版日期2011-11
- 单位浙江工业大学
