Paper Title:
A Stochastic Disturbance of Particle Swarm Optimization for K-Means Clustering Method
| Periodical | Advanced Materials Research (Volumes 268 - 270) |
|---|---|
| Main Theme | Computational Materials Science |
| Edited by | Feng Xiong |
| Pages | 10-15 |
| DOI | 10.4028/www.scientific.net/AMR.268-270.10 |
| Citation | Jun Yan Chen, 2011, Advanced Materials Research, 268-270, 10 |
| Online since | July, 2011 |
| Authors | Jun Yan Chen |
| Keywords | K-Means Algorithm, Particle Swarm Optimization Clustering, Stochastic Disturbance |
| Price | US$ 28,- |
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Abstract
This paper presents a hybrid-clustering algorithm that is a stochastic disturbance of particle swarm optimization (PSO) for K-means clustering method (SDPSO-K). The proposed algorithm can improve the particle global searching ability in PSO to avoid the K-means disadvantage of being easily trapped in a local optimal solution and to save the expensive computational cost of PSO clustering. The performance of the SDPSO-K, compared with three recently developed modified PSO techniques and related clustering algorithms for six datasets, indicates that the SDPSO-K algorithm is clearly and consistently superior in terms of precision and robustness.
