Computer Science ›› 2016, Vol. 43 ›› Issue (8): 267-272.doi: 10.11896/j.issn.1002-137X.2016.08.054

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Fuzzy c-means and Adaptive PSO Based Fuzzy Clustering Algorithm

GENG Zong-ke, WANG Chang-bin and ZHANG Zhen-guo   

  • Online:2018-12-01 Published:2018-12-01

Abstract: The existing PSO fuzzy clustering algorithms need to set the PSO parameters and converge very slowly,a fuzzy c-means and adaptive PSO based fuzzy clustering algorithm was proposed for that problem.Firstly,the fuzzy c-means algorithm is used to generate the initial solution,leading to a more directed search process.Then,the improved adaptive PSO is used to train and optimize the dataset,and the PSO parameters are adjusted adaptively in the training process to achieve a better optimal result. Lastly,the fuzzy c-means algorithm is used for fuzzy clustering.Compared experiments results show that the proposed method improves computational speed greatly and achieve good clustering performance.

Key words: Particle swarm optimization,Parameter adjustment,Fuzzy clustering algorithm,Aadaptively adjustment,Convergence speed

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