改进的粗糙集模糊聚类算法及其应用

通过将粗糙集和模糊聚类算法相结合, 利用粗糙集中上近似集和下近似集的概念改进模糊聚类算法, 解决了模糊聚类边界不确定的问题, 得到了上近似集和下近似集的聚类结果, 从而实现更好的聚类, 改进算法可以处理边界问题和复杂数据问题. 将改进的粗糙集模糊聚类算法用于研究环糊精聚类, 并将聚类结果与K均值聚类分析算法、 模糊C均值聚类算法相比, 实验结果表明, 改进算法有较好的聚类效果.

Application of Improved Rough Set Fuzzy Clustering Algorithm

An improved algorithm was proposed which combined rough set algorithm with fuzzy clustering algorithm. The algorithm took full advantage of lower approximation set and upper approximation set in rough set to solve the problem of uncertain border of fuzzy clustering, gettingthe result of cluster in lower approximation set and upper approximation set so as to achieve better clustering. It can deal with border issuesand complex data issues. The proposed algorithm was applied to researching on cyclodextrin clustering, with the results showing that compared with K-means clustering algorithm and fuzzy C-means clustering algorithm, improved algorithm has a better clustering effect.