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• W2561954224 abstract "Differential evolution algorithm has seen various changes through numerous researches. Performance of the various algorithms depends on the changes in mutation and crossover strategies. Here in this paper, we are proposing a new variant of differential evolution named Forced Strategy Differential Evolution (FSDE), by creating a new mutation strategy. This strategy uses two parameters for mutation: a constant parameter and a variable parameter. FSDE will be applied on clustering using the k means technique. Experiments were conducted for various standard benchmark functions. FSDE was compared with the classical DE, GA and PSO in the field of clustering and the cluster quality results are tabulated. The results obtained show that the strategy implemented is more efficient than the other mutation strategies." @default.
• W2561954224 created "2017-01-06" @default.
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• W2561954224 date "2019-01-01" @default.
• W2561954224 modified "2023-09-25" @default.
• W2561954224 title "FSDE-Forced Strategy Differential Evolution used for data clustering" @default.
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• W2561954224 doi "https://doi.org/10.1016/j.jksuci.2016.12.005" @default.
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