计算机与现代化Issue(2)：7-14,8.DOI:10.3969/j.issn.1006-2475.2024.02.002
嵌入翻筋斗策略的自适应秃鹰搜索算法及其应用
Adaptive Bald Eagle Search Algorithm Embedded with Somersault Foraging and Application
摘要
Abstract
An improved bald eagle search algorithm is proposed to address the problems that the bald eagle search(BES)algo-rithm is easy to slip into local optimum and low solution accuracy.Firstly,a Circle chaotic map is used in place of the original al-gorithm's randomly generated initial population to increase the initial population's diversity.Secondly,in the search selection space phase,adaptive weight is combined to update the bald eagle individual position and balance the search and development ability of the algorithm.Finally,the elite differential variation is fused with a somersault foraging strategy and is used to update the positions generated by bald eagle leader individuals in the subsequent stages.The ability of the algorithm to jump out of local optimum is improved.The method underwent comparative simulation tests in some standard test functions,and the Random For-est classification parameters were optimized using the suggested strategy in this research.The experimental results demonstrate that the improved algorithm outperforms the conventional algorithm in terms of solution efficiency,solution accuracy,and classi-fication accuracy.关键词
秃鹰搜索算法/Circle混沌映射/自适应权重/翻筋斗觅食策略/精英差分变异Key words
bald eagle search algorithm/Circle chaotic map/adaptive weight/somersault foraging strategy/elite differential mutation分类
信息技术与安全科学引用本文复制引用
夏煌智,陈丽敏,毛雪迪,祁富..嵌入翻筋斗策略的自适应秃鹰搜索算法及其应用[J].计算机与现代化,2024,(2):7-14,8.基金项目
黑龙江省自然科学基金资助项目(LH2019F051) （LH2019F051）
黑龙江省高等教育教学改革重点委托项目(SJGZ20200175) （SJGZ20200175）
牡丹江师范学院研究生科技创新重点项目(kjcx2022-019mdjnu) （kjcx2022-019mdjnu）
牡丹江师范学院研究生科技创新项目(kjcx2022-097mdjnu) （kjcx2022-097mdjnu）
