Collective adaptation evolution of weighted complex networks: on syncronizability dependence

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IEEE

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info:eu-repo/semantics/closedAccess

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An innovated evolving network representation model to characterize weighted, complex, scale-free networks is proposed. A new node or a community is added to network in the process of evolution while emergences of new links occur according to the 'Triad Formation' possessing symmetry and the random selection mechanism. A weighted scale-free network with high-value clustering coefficient can be obtained by adjusting two parameters only. The evolution of degree, strength, weights exhibit the power-law distributions. Highly correlated with the degree, the average strength displays scale-free property. The average clustering coefficient is found to exhibit well power-law decay as a function of the node degree. Triad Formation and Community Structure in weighted scale-free evolving networks, as building mechanisms, can distinctly enhance the clustering coefficient of networks. Both type I and type II networks are found their synchronizability to decrease as the average clustering coefficient increases in weighted scale-free networks of communities.

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Dimirovski, Georgi M. (Dogus Author) -- Conference full title: 13th IEEE International Conference on Control and Automation, ICCA 2017; Ohrid; Macedonia; 3 July 2017 through 6 July 2017.

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Clustering Coefficient, Collective Adaptation, Community Structures, Complex Networks

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13th IEEE International Conference on Control & Automation

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Jing, Y., Wang, D., & Dimirovski, G. M. (2017). Collective adaptation evolution of weighted complex networks: on syncronizability dependence. In 13th IEEE International Conference on Control and Automation (pp. 88-93). Ohrid: IEEE. http://dx.doi.org/10.1109/ICCA.2017.8003040

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