Integrating Nature-inspired Optimization Algorithms to K-means Clustering
Rui Tang1; Simon Fong1; Xin-She Yang2; Suash Deb3
Conference NameSeventh International Conference on Digital Information Management (ICDIM 2012)
Source Publication7th International Conference on Digital Information Management, ICDIM 2012
Conference Date22-24 Aug. 2012
Conference PlaceMacau, China

Although K-means clustering algorithm is simple and popular, it has a fundamental drawback of falling into local optima that depend on the randomly generated initial centroid values. Optimization algorithms are well known for their ability to guide iterative computation in searching for global optima. They also speed up the clustering process by achieving early convergence. Contemporary optimization algorithms inspired by biology, including the Wolf, Firefly, Cuckoo, Bat and Ant algorithms, simulate swarm behavior in which peers are attracted while steering towards a global objective. It is found that these bio-inspired algorithms have their own virtues and could be logically integrated into K-means clustering to avoid local optima during iteration to convergence. In this paper, the constructs of the integration of bio-inspired optimization methods into K-means clustering are presented. The extended versions of clustering algorithms integrated with bio-inspired optimization methods produce improved results. Experiments are conducted to validate the benefits of the proposed approach. 

KeywordAnt Colony Optimization Bat Optimization Cuckoo Optimization Firefly Optimization K-means Clustering Algorithm Wolf Search Optimization
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Department of Computer and Information Science University of Macau Taipa, Macau SAR
2.Mathematics and Scientific Computing National Physical Laboratory Teddington, UK
3.Department of Computer Science & Engineering C. V. Raman College of Engineering Bidyanagar, India
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Rui Tang,Simon Fong,Xin-She Yang,et al. Integrating Nature-inspired Optimization Algorithms to K-means Clustering[C]:IEEE,2012:116-123.
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