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- 2013-10-14
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Description: In this paper, a novel Discrete Particle Swarm Optimization Algorithm
(DPSOA) for data clustering has been proposed. The particle positions and velocities
are defined in a discrete form. The DPSOA algorithm uses of a simple probability
approach to construct the velocity of particle followed by a search scheme to
constructs the clustering solution. DPSOA 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 results obtained by
the proposed algorithm have been compared with the published results of Basic
PSO (B-PSO) algorithm, Genetic Algorithm (GA), Differential Evolution (DE) algorithm
and Combinatorial Particle Swarm Optimization (CPSO) algorithm. The
performance analysis demonstrates the effectiveness of the proposed algorithm in
solving the partitional data clustering problems.
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