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We introduce a minimal extended evolving model for small-world networks which is controlled by a parameter. In this model the network growth is determined by the attachment of new nodes to already existing nodes that are geographically close. We analyze several topological properties for our model both analytically and by numerical simulations. The(More)
In order to mimic complex real-life systems, in this paper, we propose evolving small-world networks based on the modified BA model. In the process of network evolution, the links among the new nodes at each time step are involved, which is different from the classic BA model. The simulation results show our model exhibits the small-world property and the(More)
We propose two types of evolving networks: evolutionary Apollonian networks (EANs) and general deterministic Apollonian networks (GDANs), established by simple iteration algorithms. We investigate the two networks by both simulation and theoretical prediction. Analytical results show that both networks follow power-law degree distributions, with(More)
Decision-makers in emergencies usually need supports of background knowledge and information for decision-making support. Emergency documentation can partially provide such supports through its effective reorganization according to various incident scenarios. This paper aims at constructing emergency ontology to support decision-making directly from such(More)
We propose an extended local-world evolving network model including a triad formation step. In the process of network evolution, random fluctuation in the number of new edges is involved. We derive analytical expressions for degree distribution, clustering coefficient and average path length. Our model can unify the generic properties of real-life networks:(More)