计算机与现代化Issue(12)：30-35,6.DOI:10.3969/j.issn.1006-2475.2023.12.006
聚类质心与指数递减方法改进的哈里斯鹰算法
Improved Harris Hawks Optimization Algorithm Based on Cluster Centroid and Exponential Decline Method
摘要
Abstract
To promote optimization performance of Harris hawks optimization algorithm,KmHHO algorithm is proposed.Firstly,all populations as a cluster,the cluster centroid is calculated with Kmeans of Matlab,mean of HHO is replaced by cluster cen-troid.Then,to control the segments of exploration and development,linearly decreasing escape energy of prey is replaced with expo-nentially decreasing escape energy of prey.Finally,searching performance of five algorithms is compared on 23 benchmark func-tions,the improved effect of KmHHO is verified and Wilcoxon rank sum test is utilized to analyze the difference of KmHHO with other four optimization algorithms.The experimental results show that among the 23 benchmarks,KmHHO can achieve the optimal value on 14 benchmark functions,and its overall performance is higher than GWO,HHO and AO,but it's equivalent to DAHHO.关键词
哈里斯鹰算法/Kmeans/指数递减/秩和检验/群体智能寻优算法Key words
Harris hawks optimization/Kmeans/exponentially decreasing/rank sum test/swarm intelligence optimization algorithm分类
计算机与自动化引用本文复制引用
白晓波,江梦茜,王铁山,邵景峰,李勃..聚类质心与指数递减方法改进的哈里斯鹰算法[J].计算机与现代化,2023,(12):30-35,6.基金项目
国家自然科学基金资助项目(71802155) （71802155）
陕西省教育厅智库项目(20JT027) （20JT027）
咸阳市重点研发计划项目(S2021ZDYF-GY-0715) （S2021ZDYF-GY-0715）
