计算机应用研究2024，Vol.41Issue(1)：116-125,10.DOI:10.19734/j.issn.1001-3695.2023.05.0185
一种基于荧光信息导航的聚类算法
Firefly luminescent information navigation clustering algorithm
王跃飞 1曾世杰 1于曦 2刘兴蕊 1李越1
作者信息
- 1. 成都大学计算机学院,成都 610106
- 2. 成都大学斯特灵学院,成都 610106
- 折叠
摘要
Abstract
Clustering is a branch of unsupervised machine learning algorithms that has widespread applications in the informa-tion age.However,diverse research on clustering algorithms often faces issues such as it need to specify a fixed number of neighbors for density calculation,the requirement of predefining the number of clusters,and the necessity for multiple iterations to update information aggregation.These problems can lead to the loss of data features and increase computational complexity,resulting in higher time complexity of the models.To address these challenges,this paper inspired by the luminescence and light information transmission of fireflies and proposed a clustering algorithm called FLINCA.FLINCA consisted of two main modules,such as growing fireflies and merging fireflies trees.Firstly,it treated data points as fireflies,and determined their brightness u-sing an adaptive number of neighbors to achieve preliminary clustering.Then,it performed cluster fusion based on the firefly trees,resulting in the final clustering outcome.Experimental results demonstrate that FLINCA exhibits favorable clustering per-formance on four benchmark clustering datasets and three real-world multidimensional datasets compared to twelve different algo-rithms.This confirms the extensive applicability of FLINCA,which is based on firefly luminescence and light information trans-mission,in addressing the limitations of traditional clustering algorithms and improving clustering accuracy.关键词
无监督聚类/仿生学/萤火虫算法Key words
unsupervised clustering/bionics/firefly algorithm分类
信息技术与安全科学引用本文复制引用
王跃飞,曾世杰,于曦,刘兴蕊,李越..一种基于荧光信息导航的聚类算法[J].计算机应用研究,2024,41(1):116-125,10.
