— This paper shows that the k-means quantization of a signal can be interpreted both as a crisp indicator function and as a fuzzy membership assignment describing fuzzy clusters ...
Abstract. We propose a new clustering algorithm satisfying requirements for the post-clustering algorithms as many as possible. The proposed “Fuzzy Concept ART” is the form of ...
Fuzzy clustering algorithms have been widely studied and applied in a variety of areas. They become the major techniques7 in cluster analysis. In this paper, we focus on objective...
The major drawback of fuzzy data mining is that after applying fuzzy data mining on the quantitative data, the number of extracted fuzzy association rules is very huge. When many ...
Marjan Kaedi, Mohammad Ali Nematbakhsh, Nasser Gha...