一种基于粒子群优化的模糊聚类算法

2007 First IEEE International Symposium on Information Technologies and Applications in Education Pub Date : 2007-12-26 DOI:10.1109/ISITAE.2007.4409243

Lili Li, Xiyu Liu, Mingming Xu

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引用次数: 47

摘要

为了克服模糊c均值算法的局部最优性和初始化敏感性等缺点，本文讨论了一种新的基于粒子群算法的模糊算法。新算法利用了粒子群算法的全局搜索能力，解决了FCM的问题。实验表明，该算法避免了局部最优，提高了收敛速度。

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A Novel Fuzzy Clustering Based on Particle Swarm Optimization

In order to overcome the shortcomings of fuzzy C-means algorithm such as the local optima and sensitivity to initialization, a new PSO-based fuzzy algorithm is discussed in this paper. The new algorithm uses the capacity of global search in PSO algorithm, and solves the problems of FCM. The experiment shows that the algorithm avoids the local optima and increases the convergence speed.

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2007 First IEEE International Symposium on Information Technologies and Applications in Education

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