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Aiming at the disadvantages of the traditional K-means clustering algorithm, a new algorithm based on density is proposed to remove the noises and outliers in this paper. This algorithm determines whether a point is a noise or not according to the density of the point. Experiments show that this algorithm can effectively eliminate the influence of the noises when the K-means algorithm searches cluster...
This paper proposes a mixed optimization algorithm based on RBF neural network (RBF) and Particle Swarm Optimization (PSO), which is applied to the doorplate recognition for a mobile robot. The centers and widths of RBF neural network are determined with self-increasing clustering algorithm, and the improved particle swarm optimization algorithm is used to optimize their distance from the threshold...
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