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- W2012258043 abstract "In this paper we propose a clustering method based on combination of the particle swarm optimization (PSO) and the k-mean algorithm. PSO algorithm was showed to successfully converge during the initial stages of a global search, but around global optimum, the search process will become very slow. On the contrary, k-means algorithm can achieve faster convergence to optimum solution. At the same time, the convergent accuracy for k-means can be higher than PSO. So in this paper, a hybrid algorithm combining particle swarm optimization (PSO) algorithm with k-means algorithm is proposed we refer to it as PSO-KM algorithm. The algorithm aims to group a given set of data into a user specified number of clusters. We evaluate the performance of the proposed algorithm using five datasets. The algorithm performance is compared to K-means and PSO clustering." @default.
- W2012258043 created "2016-06-24" @default.
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- W2012258043 date "2008-08-01" @default.
- W2012258043 modified "2023-09-27" @default.
- W2012258043 title "Combining PSO and k-means to enhance data clustering" @default.
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- W2012258043 doi "https://doi.org/10.1109/istel.2008.4651388" @default.
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