排序方式: 共有31条查询结果,搜索用时 312 毫秒
31.
Vidyut Dey Dilip Kumar Pratihar G. L. Datta 《Fuzzy Optimization and Decision Making》2011,10(2):153-166
A modified approach had been developed in this study by combining two well-known algorithms of clustering, namely fuzzy c-means
algorithm and entropy-based algorithm. Fuzzy c-means algorithm is one of the most popular algorithms for fuzzy clustering.
It could yield compact clusters but might not be able to generate distinct clusters. On the other hand, entropy-based algorithm
could obtain distinct clusters, which might not be compact. However, the clusters need to be both distinct as well as compact.
The present paper proposes a modified approach of clustering by combining the above two algorithms. A genetic algorithm was
utilized for tuning of all three clustering algorithms separately. The proposed approach was found to yield both distinct
as well as compact clusters on two data sets. 相似文献