期刊
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
卷 46, 期 3, 页码 562-576出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207721.2013.797037
关键词
hesitant fuzzy set; agglomerative hierarchical clustering; interval-valued hesitant fuzzy set; hesitant fuzzy distance
类别
资金
- National Natural Science Foundation of China [71071161, 61273209]
Recently, hesitant fuzzy sets (HFSs) have been studied by many researchers as a powerful tool to describe and deal with uncertain data, but relatively, very few studies focus on the clustering analysis of HFSs. In this paper, we propose a novel hesitant fuzzy agglomerative hierarchical clustering algorithm for HFSs. The algorithm considers each of the given HFSs as a unique cluster in the first stage, and then compares each pair of the HFSs by utilising the weighted Hamming distance or the weighted Euclidean distance. The two clusters with smaller distance are jointed. The procedure is then repeated time and again until the desirable number of clusters is achieved. Moreover, we extend the algorithm to cluster the interval-valued hesitant fuzzy sets, and finally illustrate the effectiveness of our clustering algorithms by experimental results.
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