应用膜计算的社区检测算法

摘要

To improve the speed and quality of community detection algorithm, proposed membrane computing-based detection algorithm. Distribution and parallelism of membrane are used to enhance the speed and quality of detection. Used label propagation and genetic rules when membrane object is evolving, realized the parallel computing of community detection. The simulation experiment was tested. Experimental results show that the algorithm is fast, accurate, and feasible. It provides a new way to community detection.%为提高社区检测算法的速度和质量,提出一种基于膜计算的检测算法.利用膜计算的分布性、并行性,来提高检测的速度和质量,膜对象进化时使用标签传播、遗传规则,实现社区检测的并行计算,并进行仿真实验.结果表明:该算法快速、准确,具有可行性,为网络的社区检测提供了一种新思路.