Fuzzy hierarchical clustering based on fuzzy dissimilarity

Y. Lv, C. K. Lee
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引用次数: 5

Abstract

This paper develops a new fuzzy hierarchical clustering method based on Agglomerative nesting with the introduction of fuzzy dissimilarity. Since normal hierarchical clustering methods only can be applied for real numbers while a set of possible values, fuzzy numbers are gathered in data collection. It's important to find an effective and efficient way for clustering so as to realize the structure of the complex data for decision making. In this research, the trapezoidal fuzzy numbers are selected in this research, and the proposed new hierarchical clustering method can be competent with the existing clustering method with the given set of fuzzy numbers.
基于模糊不相似度的模糊层次聚类
提出了一种基于聚类嵌套的模糊层次聚类方法。由于普通的层次聚类方法只能对实数进行聚类,而在数据收集过程中会收集到一组可能的值,因此在数据收集过程中会收集到模糊数。寻找一种有效的聚类方法来实现复杂数据的结构,为决策提供依据是非常重要的。在本研究中,选取了梯形模糊数,在给定的模糊数集合下,本文提出的分层聚类方法可以胜任现有的聚类方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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