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Local Events and Dynamics on Weighted Complex Networks

Local Events and Dynamics on Weighted Complex Networks
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摘要 We examine the weighted networks grown and evolved by local events, such as the addition of new vertices and links and we show that depending on frequency of the events, a generalized power-law distribution of strength can emerge. Continuum theory is used to predict the scaling function as well as the exponents, which is in good agreement with the numerical simulation results. Depending on event frequency, power-law distributions of degree and weight can also be expected. Probability saturation phenomena for small strength and degree in many real world networks can be reproduced. Particularly, the non-trivial clustering coefficient, assortativity coefficient and degree-strength correlation in our model are all consistent with empirical evidences. We examine the weighted networks grown and evolved by local events, such as the addition of new vertices and links and we show that depending on frequency of the events, a generalized power-law distribution of strength can emerge. Continuum theory is used to predict the scaling function as well as the exponents, which is in good agreement with the numerical simulation results. Depending on event frequency, power-law distributions of degree and weight can also be expected. Probability saturation phenomena for small strength and degree in many real world networks can be reproduced. Particularly, the non-trivial clustering coefficient, assortativity coefficient and degree-strength correlation in our model are all consistent with empirical evidences.
作者 赵晖 高自友
出处 《Chinese Physics Letters》 SCIE CAS CSCD 2006年第8期2311-2314,共4页 中国物理快报(英文版)
基金 Supported by the National 0utstanding Young Investigator of the National Natural Science Foundation of China Grant under Nos 70225005 and 70471088, and the Doctoral Station Programme of the Ministry of Education of China (20050004005).
关键词 EVOLVING NETWORKS TOPOLOGY EVOLVING NETWORKS TOPOLOGY
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参考文献21

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