荆楚理工学院学报2026，Vol.41Issue(2)：48-56,9.
多策略人工蜂鸟算法的特征选择方法
Feature Selection Method Based on Multi-strategy Artificial Hummingbird Algorithm
摘要
Abstract
A multi-strategy artificial hummingbird algorithm(MAHA)is proposed to address the issues of low accuracy and susceptibility to local optima in the iterative process of the artificial hummingbird algorithm.Kent chaotic mapping is introduced during the initialization phase of hummingbird population to improve population diversity and distribution uniformity,thereby en-hancing the algorithm's exploration capability.A differential mutation strategy is applied to update the positions of hummingbirds so that they can escape from local optima.Levy flight improvement algorithm is adopted to enhance the quality of candidate solutions,thus improving convergence speed and accuracy.The MAHA and classical intelligent optimization algorithms were tested on 9 benchmark functions and 6 UCI datasets,and the results shows that MAHA exhibited excellent performance in both accuracy and convergence speed.The feature selection method based on MAHA significantly outperforms other comparative algorithms in classi-fication accuracy and performance.关键词
人工蜂鸟算法/混沌映射/差分变异/Levy飞行策略/特征选择Key words
artificial hummingbird algorithm/chaotic mapping/differential mutation/levy flight strategy/feature selection分类
信息技术与安全科学引用本文复制引用
崔心惠,袁荣荣,陶璐,胡瑞..多策略人工蜂鸟算法的特征选择方法[J].荆楚理工学院学报,2026,41(2):48-56,9.基金项目
安徽省教育厅高校自科重大项目﹙2024AH040204) （）
安徽省一流核心示范金课﹙2024yljk056) （）
滁州职业技术学院第一批高层次人才自科项目﹙DQJ-2024-2) （）
滁州职业技术学院自科一般项目﹙ZKY-2023-1) （）
