Data Clustering using almost parameter free Differential Evolution technique

Abstract

The paper presents a comparative analysis of data clustering by Particle swarm optimization (PSO) and differential evolution (DE) techniques. It is clearly reveled from the simulation results that almost parameter free optimization technique such as Differential evolution could provide better performance compared to PSO where in many parameters are to be tuned. To exhibit the numerical optimizing capability of DE we have demonstrated the capability of this by optimizing few benchmark functions.

Reference

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