A Multiagent Memetic Optimization Algorithm Based on Temporal Asymptotic Surprise in Complex Networks to Reveal the Structure of the Dynamic Community

Author:

Ranjkesh Somayeh1ORCID,Masoumi Behrooz2ORCID,Hashemi Seyyed Mohsen1

Affiliation:

1. Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

2. Faculty of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract

Complex networks are used in a variety of applications. Revealing the structure of a community is one of the essential features of a network, during which remote communities are discovered in a complex network. In the real world, dynamic networks are evolving, and the problem of tracking and detecting communities at different time intervals is raised. We can use dynamic graphs to model these types of networks. This paper proposes a multiagent optimization memetic algorithm in complex networks to detect dynamic communities and calls it DYNMAMA (dynamic multiagent memetic algorithm). The temporal asymptotic surprise is used as an evaluation function of the algorithm. In the proposed algorithm, work is done on dynamic data. This algorithm does not need to specify the number of communities in advance and meets the time smoothing limit, and this applies to dynamic real-world and synthetic networks. The results of the performance of the evaluation function show that this proposed algorithm can find an optimal and more convergent solution compared to modern approaches.

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Security Evaluation Method for Complex Computer Networks Based on GABP Algorithm;2023 World Conference on Communication & Computing (WCONF);2023-07-14

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