A Hybrid Bumble Bees Mating Optimization - GRASP Algorithm for Clustering

被引：0
|
作者：
Marinakis, Yannis [1 ]
Marinaki, Magdalene [2 ]
Matsatsinis, Nikolaos [1 ]
机构：
[1] Tech Univ Crete, Decis Support Syst Lab, Dept Prod Engn & Management, Khania 73100, Greece
[2] Tech Univ Crete, Dept Prod Engn & Management, Ind Syst Control Lab, Iraklion, Greece
来源：
HYBRID ARTIFICIAL INTELLIGENCE SYSTEMS | 2009年 / 5572卷
关键词：
Bumble Bees Mating Optimization; Greedy Randomized Adaptive Search Procedure; Clustering Analysis;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new hybrid algorithm for clustering, which is based on the concepts of the Bumble Bees Mating Optimization (BBMO) and Greedy Randomized Adaptive Search Procedure (GRASP), is presented in this paper. The proposed algorithm is a two phase algorithm which combines a new algorithm called Bumble Bees Mating Optimization algorithm for the solution of the feature selection problem and a GRASP algorithm for the solution of the clustering problem. The performance of the algorithm is compared with other popular metaheuristic and nature inspired methods using datasets from the UCI Machine Learning Repository. The high performance of the proposed algorithm is achieved as the algorithm gives very good results and in some instances the percentage of the correct. clustered samples is very high and is larger than 98%.
引用
收藏
页码：549 / +
页数：2
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