In this algorithm, the cluster center is simulated as a particle. Cloning and mutation operations are used to increase the diversity and improve the global ...
The results show that the improved algorithm not only ensures the global convergence of the algorithm, but also obtains more accurate clustering results.
In the paper "K-means clustering based on improved quantum particle swarm optimization algorithm", the authors used the k-means algorithm for faster convergence ...
This paper discusses the current improvement in the QPSO-k-means clustering algorithm, focusing on swarm initialisation and algorithm parameter optimisation. We ...
The original K-means clustering algorithm is seriously affected by initial centroids of clustering and easy to fall into local optima.
Jul 8, 2023 · This paper discusses the current improvement in the QPSO-k-means clustering algorithm, focusing on swarm initialisation and algorithm parameter ...
The aim of this paper is to establish the optimal algorithm for data analysis by means of the research on the improved hybrid clustering algorithm of particle ...
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This paper presents a new hybrid algorithm named DPSOK to obtain better image segmentation. It is based on an improved PSO and K-means.
The aim of this paper is to establish the optimal algorithm for data analysis by means of the research on the improved hybrid clustering algorithm of particle ...
Sep 5, 2020 · We present an efficient hybrid clustering algorithm referred to as QALO-K, whereby, we combine k-means with quantum-inspired ant lion optimized.