This paper presents the concepts of isomorphism and homomorphism of fuzzy sets (fuzzy relation), gives sufficient and necessary conditions of isomorphism ...
We propose the concept of classified isomorphism of the fuzzy relation and prove that if two fuzzy similarity relation are isomorphic, then they must be ...
This paper presents a formalization of cluster extraction algoritmus for an asymmetric fuzzy data, i.e. a fuzzy digraph, and its applications to instructional ...
Abstract: This paper presents the concepts of isomorphism and homomorphism of fuzzy sets (fuzzy relation), gives sufficient and necessary conditions of ...
Nov 1, 2023 · Fuzzy clustering is a type of clustering algorithm in machine learning that allows a data point to belong to more than one cluster with different degrees of ...
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This paper is a survey of fuzzy set theory applied in cluster analysis. These fuzzy clustering algorithms have been widely studied and applied in a variety of ...
One of the major challenges in unsupervised clustering is the lack of consistent means for assessing the quality of clusters. In this paper, we evaluate ...
On Consistency of Fuzzy Clustering Analysis. Zhang Cheng-yi, Wei Bencheng, Chen Guohui · Details · Contributors · Bibliography · Quotations · Similar ...
This paper proposes a fuzzy modeling method via Enhanced Objective Cluster Analysis to obtain the compact and robust approximate TSK fuzzy model.
This paper studies the fuzzy C-means clustering in which the model proposed by Bezdek is a typical representative and finds that they are consistent in ...