摘要: 针对原始吸引模型及改进模型存在聚集系数小的缺陷,提出一种基于聚类效应节点吸引力的复杂网络模型CALW。该模型针对真实网络中择优连接的局域性特点,借鉴森林火灾传播的思想构造局域世界,将节点的吸引力定义为随时间变化的函数。数值模拟结果表明,CALW模型的度分布服从幂律分布,具有较高的网络聚集系数,且有保持高聚集性不变的特性。
关键词:
复杂网络,
局域世界,
无标度,
聚类效应,
节点吸引力
Abstract: Aiming at the disadvantage of low clustering coefficient in initial attractive model proposed by Dorogovtsev and its extended model, a complex network evolving model based on node attraction with clustering effect(CALW model) is proposed. According to the local-world property of preferential attachment existed in real networks, CALW model constructs local-world by referencing on the idea of forest fire, and defines node attraction as a dynamic function with the change. Simulation results show that the network generated by CALW model follows power-law degree distribution.
Key words:
complex network,
local-world,
scale-free,
clustering effect,
node attraction
中图分类号:
田生文;杨洪勇;李阿丽;王伊蕾. 基于聚类效应节点吸引力的复杂网络模型[J]. 计算机工程, 2010, 36(10): 58-60.
TIAN Sheng-wen; YANG Hong-yong; LI A-li; WANG Yi-lei. Complex Network Model Based on Node Attraction with Clustering Effect[J]. Computer Engineering, 2010, 36(10): 58-60.