A new logistic map based chaotic biogeography-based optimization approach for cluster analysis

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave...

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Bibliographic Details
Published in2016 International Conference on Progress in Informatics and Computing (PIC) pp. 88 - 92
Main Authors Shui-Hua Wang, Hui-Min Lu, Yu-Jie Li, Yang Wang, Zhi-Min Chen, Yu-Min Wei, Wen-Juan Jia, Fang-Yuan Liu, Yu-Dong Zhang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Algorithm design and analysis
centroid-based clustering
chaotic biogeography-based optimization
cluster analysis
Clustering algorithms
Genetic algorithms
Logistics
Mathematical model
Optimization
Particle swarm optimization
simulation
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Summary:Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.
DOI:10.1109/PIC.2016.7949472