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鲸鱼优化算法研究与应用进展

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鲸鱼优化算法 WOA是一种根据概率收敛的新型群体智能优化算法,具有原理简单易实现、参数量少易设置和全局与局部开发分别控制易平衡等特点.系统地分析 WOA的基本原理和算法性能影响因素,重点论述现有的算法改进策略和算法混合策略的优点及局限性,并阐述了 WOA 在支持向量机、人工神经网络、组合优化和复杂函数优化等方面的应用与发展.最后,结合 WOA 的特点及其应用成果,对 WOA的发展方向进行了展望.
Research and application of whale optimization algorithm
The Whale Optimization Algorithm(WOA)is a novel swarm intelligence optimization al-gorithm that converges based on probability.It features simple and easily implementable algorithm prin-ciples,a small number of easily adjustable parameters,and a balance between global and local search control.This paper systematically analyzes the basic principles of WOA and factors influencing algo-rithm performance.It focuses on discussing the advantages and limitations of existing algorithm im-provement strategies and hybrid strategies.Additionally,the paper elaborates on the applications and developments of WOA in support vector machines,artificial neural networks,combinatorial optimiza-tion,complex function optimization,and other areas.Finally,considering the characteristics of WOA and its research achievements in applications,the paper provides a prospective outlook on the research and development directions of WOA.

whale optimization algorithmswarm intelligencesearch mechanismimprovement strat-egy

王颍超

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北京理工大学网络空间安全学院,北京 100081

鲸鱼优化算法 群体智能 搜索机制 改进策略

国家重点研发计划

2021YFB1715700

2024

计算机工程与科学
国防科学技术大学计算机学院

计算机工程与科学

CSTPCD北大核心
影响因子:0.787
ISSN:1007-130X
年,卷(期):2024.46(5)
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