Publication Type:

Conference Proceedings

Source:

COMPUTE '09 Proceedings of the 2nd Bangalore Annual Compute Conference, ACM, Volume 16, New York, NY, USA (2009)

ISBN:

9781605584768

URL:

http://doi.acm.org/10.1145/1517303.1517321

Keywords:

Data clustering, particle swarm optimization, TRace Within criterion, variance ratio criterion

Abstract:

In this paper, a novel Discrete Particle Swarm Clustering algorithm (DPSC) for data clustering has been proposed. The particle positions and velocities are defined in a discrete form and an efficient approach is developed to move the particles for constructing new clustering solutions. DPSC algorithm has been applied to solve the data clustering problems by considering two performance metrics, such as TRace Within criteria (TRW) and Variance Ratio Criteria (VRC). The result obtained by the proposed algorithm has been compared with the published results of Combinatorial Particle Swarm Optimization (CPSO) algorithm and Genetic Algorithm (GA). The performance analysis demonstrates the effectiveness of the proposed algorithm in solving the partitional data clustering problems.

Cite this Research Publication

R. Karthi, Arumugam, S., and Rameshkumar, K., “A Novel Discrete Particle Swarm Clustering Algorithm for Data Clustering”, COMPUTE '09 Proceedings of the 2nd Bangalore Annual Compute Conference, vol. 16. ACM, New York, NY, USA, 2009.

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