Ju Ying, Zhang Songming, Ding Ningxiang, Zeng Xiangxiang, Zhang Xingyi
School of Information Science and Technology, Xiamen University, Xiamen, China.
School of Computer Science and Technology, Anhui University, Anhui, China.
Sci Rep. 2016 Sep 27;6:33870. doi: 10.1038/srep33870.
The field of complex network clustering is gaining considerable attention in recent years. In this study, a multi-objective evolutionary algorithm based on membranes is proposed to solve the network clustering problem. Population are divided into different membrane structures on average. The evolutionary algorithm is carried out in the membrane structures. The population are eliminated by the vector of membranes. In the proposed method, two evaluation objectives termed as Kernel J-means and Ratio Cut are to be minimized. Extensive experimental studies comparison with state-of-the-art algorithms proves that the proposed algorithm is effective and promising.
近年来，复杂网络聚类领域受到了广泛关注。在本研究中，提出了一种基于膜的多目标进化算法来解决网络聚类问题。种群平均被划分为不同的膜结构。进化算法在这些膜结构中进行。种群通过膜向量被淘汰。在所提出的方法中，两个被称为核J均值和比率切割的评估目标要被最小化。与现有最先进算法的广泛实验研究比较证明了所提出的算法是有效且有前景的。
