Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
412849 | Neurocomputing | 2010 | 4 Pages |
Abstract
In this paper, we propose a new rewiring rule that generates small-world networks with larger clustering coefficient and smaller average path length. Unlike the random rewiring rule in the WS model described by Watts and Strogatz, we use the “rich-gets-richer” rule that links a vertex that already has a large number of connections and has a higher probability. Simulation results also verify that the novel “rich-gets-richer” rule based small-world network is an improvement over the WS model.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Hongwei Dai, Shangce Gao, Yu Yang, Zheng Tang,