Intuitionistic fuzzy hierarchical clustering algorithms |
| |
Authors: | Xu Zeshui |
| |
Affiliation: | Coll. of Economics and Management, Southeast Univ., Nanjing 210096, P. R. China;Inst. of Sciences, PLA Univ. of Science and Technology, Nanjing 210007, P. R. China |
| |
Abstract: | Intuitionistic fuzzy set (IFS) is a set of 2-tuple arguments, each of which is characterized by a mem-bership degree and a nonmembership degree. The generalized form of IFS is interval-valued intuitionistic fuzzy set (IVIFS), whose components are intervals rather than exact numbers. IFSs and IVIFSs have been found to be very useful to describe vagueness and uncertainty. However, it seems that little attention has been focused on the clus-tering analysis of IFSs and IVIFSs. An intuitionistic fuzzy hierarchical algorithm is introduced for clustering IFSs, which is based on the traditional hierarchical clustering procedure, the intuitionistic fuzzy aggregation operator, and the basic distance measures between IFSs: the Hamming distance, normalized Hamming, weighted Hamming, the Euclidean distance, the normalized Euclidean distance, and the weighted Euclidean distance. Subsequently, the algorithm is extended for clustering IVIFSs. Finally the algorithm and its extended form are applied to the classifications of building materials and enterprises respectively. |
| |
Keywords: | intuitionistic fuzzy set interval-valued intuitionistic fuzzy set hierarchical clustering intuitionistic fuzzy aggregation operator distance measure. |
本文献已被 维普 万方数据 等数据库收录! |
| 点击此处可从《系统工程与电子技术(英文版)》浏览原始摘要信息 |
|
点击此处可从《系统工程与电子技术(英文版)》下载免费的PDF全文 |
|