Community Detection Algorithm Based on Single Target PSO

摘要

With the development of information technology, complex networks have become more common in people's lives, and methods based on modularity optimization have attracted more and more attention. Because the traditional particle swarm algorithm is used to solve continuous optimization problems, the community structure detection problem is a discrete optimization problem based on graphs. We applied a new coding strategy and a particle update strategy to overcome this problem. In the update strategy, we introduced a method based on neighbor update to ensure that the update of the particles is guided to a certain extent by following the neighborhood information, which is in line with the characteristics of real complex networks. In addition, the expanded module density function is used for optimization to overcome the resolution limitation problem of the traditional module density function and to ensure that the community structure of complex networks is found at different resolutions.