| 引用本文: | 王丹,吴孟达.粗糙模糊C均值融合聚类.[J].国防科技大学学报,2011,33(3):145-150.[点击复制] |
| WANG Dan,WU Mengda.Rough Fuzzy C-Means Combination Clustering[J].Journal of National University of Defense Technology,2011,33(3):145-150[点击复制] |
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| 粗糙模糊C均值融合聚类 |
| 王丹, 吴孟达 |
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(国防科技大学 理学院，湖南 长沙 410073)
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| 摘要: |
| 提出一种新的粗糙模糊C均值融合聚类算法，该算法通过粗糙集上、下近似的引入改变了模糊C均值算法中隶属度函数的分布情况，修正了类心的更新公式和模糊隶属度计算公式，降低了计算复杂度，在改变模糊隶属度分布的同时，通过使得每一类总的隶属度变化保持最小，进一步提出了边界调节参数的自适应选择算法，实验结果表明，粗糙模糊C均值融合算法具有较好的效果。 |
| 关键词: 模糊C均值聚类 粗糙集 粗糙模糊C均值聚类 |
| DOI： |
| 投稿日期：2010-10-18 |
| 基金项目:国家自然科学基金资助项目(60872152) |
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| Rough Fuzzy C-Means Combination Clustering |
| WANG Dan, WU Mengda |
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(College of Science, National Univ. of Defense Technology, Changsha 410073, China)
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| Abstract: |
| A deep-seated rough fuzzy C-Means combined (RFCMC) clustering algorithm is proposed. The algorithm alters the distribution of fuzzy membership function by combining the lower approximation and upper approximation. Accordingly, the computation of class centroid and fuzzy membership is modified. Moreover, a self-adaptive adjusting edge parameter algorithm is prepresented. The results from experiments prove the improved effects. |
| Keywords: fuzzy C-Means clustering rough sets rough fuzzy C-Means clustering |
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