| 两阶段模糊C-均值聚类算法 |
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| 引用本文： | 张新波.两阶段模糊C-均值聚类算法[J].电路与系统学报,2005,10(2):117-120. |
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| 作者姓名： | 张新波 |
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| 作者单位： | 浙江工商大学,信息与电子工程学院,浙江,杭州,310035 |
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| 基金项目： | 国家自然科学基金资助项目(79970037)，浙江省教育厅资助项目(20041345) |
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| 摘 要： | 针对模糊C-均值(Fuzzy C-Means,FCM)算法对初始值敏感、收敛结果易陷入局部极小的问题,本文提出了一种新型的两阶段模糊C-均值聚类算法。算法提出了一种简洁快速的初始聚类中心的选取规则,从而使获得的聚类结果为全局最优。仿真结果证明了该算法的有效性和优越性。
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| 关 键 词： | 模糊聚类 FCM算法 局部极小 初始聚类中心 全局最优解 |
| 文章编号： | 1007-0249(2005)02-0117-04 |
| 修稿时间： | 2003年9月7日 |
Fuzzy C-Means clustering algorithm with two stages |
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| ZHANG Xin-bo.Fuzzy C-Means clustering algorithm with two stages[J].Journal of Circuits and Systems,2005,10(2):117-120. |
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| Authors: | ZHANG Xin-bo |
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| Abstract: | Fuzzy C-Means is one of the algorithms for clustering based on optimizing an objective function, being sensitive to initial conditions, the algorithm usually leads to local minimum results. Aiming at above problem, this paper proposes a new FCM algorithm with two stages. The new algorithm can obtain global optimal solutions through a new simple and efficient select rule of the initial cluster centers. The computer emulate results show the effectivity and superiority of the new algorithm. |
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| Keywords: | fuzzy clustering Fuzzy C-Means algorithm local minimum initial cluster centers global optimal solutions |
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