A Novel Fuzzy Clustering Based on Particle Swarm Optimization

Lili Li, Xiyu Liu, Mingming Xu
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引用次数: 47

Abstract

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.
一种基于粒子群优化的模糊聚类算法
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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