计算机应用研究2023，Vol.40Issue(12)：3584-3591,8.DOI:10.19734/j.issn.1001-3695.2023.05.0153
改进的堆优化算法及其宫颈细胞数据聚类优化
Improved heap-based optimizer and its application to cervical cell data clustering optimization
摘要
Abstract
In view of the easy entrapment into local optima and sensitiveness to initial point of conventional clustering me-thods,this paper proposed an improved heap based optimizer(HBO)clustering method.Firstly,this paper presented an improved HBO,namely DRHBO.It used a random dimensional value replacement and Gaussian disturbance strategy to update the state of the best agent to solve the defects such as low efficiency of HBO.It utilized a sine differential disturbance to update a random agent'state and that breaks through the shackle of the individual's communication only with its direct leader and colleagues,to improve the search ability.It integrated the random dimensional value replacement and differential disturbance strategies to update the states of the agents in the initial stage of HBO to avoid generating inefficient solutions.Secondly,this paper presen-ted a DRHBO clustering method and applied it to cervical cell data to get better effects.Lots of experimental results on cervical cell data sets with diverse types and different sample numbers show that compared with HBO,its variants and other state-of-the-art algorithms,DRHBO can get better performance,stronger stability and higher efficiency.DRHBO clustering is more suitable to cervical cell data.关键词
智能优化算法/堆优化算法/聚类/宫颈细胞/宫颈癌Key words
intelligent optimization algorithm/heap based optimizer(HBO)/clustering/cervical cell/cervical cancer分类
信息技术与安全科学引用本文复制引用
张新明,陈海燕,窦育强,王善侠,刘国奇,窦智,张贝..改进的堆优化算法及其宫颈细胞数据聚类优化[J].计算机应用研究,2023,40(12):3584-3591,8.基金项目
国家自然科学基金资助项目(61901160) （61901160）
