计算机应用研究2024，Vol.41Issue(4)：1086-1093,8.DOI:10.19734/j.issn.1001-3695.2023.08.0368
融入武装部队的鲸鱼优化算法用于社区发现
Whale optimization algorithm incorporating armed forces collaboration for community discovery
摘要
Abstract
Aiming at the problems of insufficient diversity of whale optimization algorithm(WO A),inefficient and unbalanced information exchange between the two search phases,this paper proposed an improved WOA based on the armed forces collabora-tive warfare mechanism for community discovery.In order to solve the problem of insufficient diversity in the encircling predation stage,this paper developed a"neighbor potential"learning model to improve the global search capability and learn breadth of WOA.To solve the problem of inefficient information exchange during the two-predation phase,this paper proposed bubble net predation based on whale commanders,which could ensure effective utilization of search information.To address the imbalance between the two predation mechanisms,this paper proposed an improved learning automaton,which could guide whale popula-tions toward promising areas.Meanwhile,because community discovery in complex networks is a discrete problem,this paper proposed a new coded discrete evolution rule based on topological properties.Finally,this paper tested the proposed algorithms on real data sets and compared them with other algorithms,and simulation experiments show that the proposed algorithm has bet-ter optimization ability than the comparison algorithm,verifying the effectiveness of the improved strategy.关键词
复杂网络/社区发现/群体智能/鲸鱼优化/部队协同Key words
complex networks/community discovery/swarm intelligence/whale optimization/force collaboration分类
信息技术与安全科学引用本文复制引用
张其文,关定坤..融入武装部队的鲸鱼优化算法用于社区发现[J].计算机应用研究,2024,41(4):1086-1093,8.基金项目
国家自然科学基金资助项目(62162040,62063021) （62162040,62063021）
