重庆理工大学学报2024，Vol.38Issue(5)：122-133,12.DOI:10.3969/j.issn.1674-8425(z).2024.03.013
一种改进鱼鹰优化算法及其应用
An improved osprey optimization algorithmand its application
摘要
Abstract
To address the poor accuracy and stability for Osprey Optimization Algorithm ( OOA) , this paper proposes some improvement strategies. First, SPM chaotic mapping has been integrated into the stage of population initialization to improve the population diversity. Second, Weibull's long and short distance random disturbances are integrated respectively in the exploration and mining stages to update the position of osprey, effectively improving the convergence accuracy of OOA. Finally, a mutation strategy of"optimum-random mean"is proposed to enhance the ability of algorithm to jump out of the local optimal during the iterative process. The proposed algorithm is called Improved Osprey Optimization Algorithm ( IOOA) . To verify the optimization ability of IOOA, it is compared with other emerging intelligent algorithms for the optimization of 12 benchmark functions. Our results show the success rate of optimization, convergence speed and stability of IOOA are significantly higher than those of other algorithms. In addition, the application of IOOA on the hyperparameter optimization of Hybrid Kernel Relevance Vector Machine is able to accurately predict the multi-objective performance of diesel engines.关键词
鱼鹰优化算法/SPM混沌映射/威布尔随机扰动/最优-随机均值变异策略Key words
osprey optimization algorithm/SPM chaotic mapping/weibull random disturbance/optimum-random mean mutation分类
信息技术与安全科学引用本文复制引用
陈曦明,张军伟,张冉,杨波,吴学雷,刘浩,毕一白..一种改进鱼鹰优化算法及其应用[J].重庆理工大学学报,2024,38(5):122-133,12.基金项目
国家自然科学基金项目(51605020) （51605020）
