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K-harmonic means clustering algorithm (KHM) is a center-based like K-means (KM), which uses the harmonic averages of the distances from each data point to the centers as components to its performance function and overcomes KM's one major drawback that is highly dependent on the initial identification of elements that represent the clusters. However, KHM is also easily trapped in local optima. In this...
In order to overcome the disadvantage that only one solution can be found in particle swarm optimization (PSO), a novel niche particle swarm multi_optimizer (multi_PSOer) which combines two strategies is devised in this paper. Firstly, guaranteed convergence PSO (GCPSO) is adopted to guarantee the algorithm can converge on a local point. Secondly, niche technique is used to ensure the algorithm is...
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