نتایج جستجو برای: fuzzy k

تعداد نتایج: 464929  

Journal: :Pattern Recognition Letters 2004
Dae-Won Kim Kwang Hyung Lee Doheon Lee

In this paper the conventional fuzzy k-modes algorithm for clustering categorical data is extended by representing the clusters of categorical data with fuzzy centroids instead of the hard-type centroids used in the original algorithm. Use of fuzzy centroids makes it possible to fully exploit the power of fuzzy sets in representing the uncertainty in the classification of categorical data. To t...

2003
Chinatsu Arima Taizo Hanai Masahiro Okamoto

The recent advances of array technologies have made it possible to monitor huge amount of genes expression data. Clustering, for example, hierarchical clustering, self-organizing maps (SOM), kmeans clustering, has become important analysis for such gene expression data. We have applied the Fuzzy adaptive resonance theory (Fuzzy ART) [5] to the gene clustering of DNA microarray data and the clus...

2005
M. M. Zahedi Lida Torkzadeh

In this note first we define the notions of intuitionistic fuzzy dual positive implicative hyper K-ideals of types 1,2,3,4 and intuitionistic fuzzy dual hyper K-ideals. Then we give some classifications about these notions according to the level subsets. Also by given some examples we show that these notions are not equivalent, however we prove some theorems which show that there are some relat...

Journal: :Bulletin of the Korean Mathematical Society 2006

2013
Asha Gowda Karegowda Seema Kumari

Data mining is the process of extracting hidden patterns from huge data. Among the various clustering algorithms, k-means is the one of most widely used clustering technique in data mining. The performance of k-means clustering depends on the initial clusters and might converge to local optimum. K-means does not guarantee the unique clustering because it generates different results with randoml...

2017
Ahtesham Husain Shaikh Manoj E. Patil C. C. Aggarwal C. K. Reddy O. M. Jafar N. A. M. Isa S. Salamah

Clustering hast two approaches, Hard clustering and soft clustering. The hard clustering restricts that the data object in the given data belongs to exactly one cluster. The problem with hard K-Means (KM) clustering is that the different initial partitions can result in different final clusters. Soft clustering which also known as fuzzy clustering forms clusters such that data object can belong...

Journal: :International journal of mathematics and computer research 2022

Fuzzy total chromatic number is the least value of k such that k-fuzzy coloring exist. In this paper, we discussed concept graphs to bistar graph and helm graph. Here define fuzzy Bistar Helm

Journal: :Journal of Korean Institute of Intelligent Systems 2008

Journal: :iranian journal of fuzzy systems 2011
khadijeh abolpour mohammad mehdi zahedi masoome golmohamadian

we present some connections between the max-min general fuzzy automaton theory and the hyper structure theory. first, we introduce a hyper bck-algebra induced by a max-min general fuzzy automaton. then, we study the properties of this hyper bck-algebra. particularly, some theorems and results for hyper bck-algebra are proved. for example, it is shown that this structure consists of different ty...

2009
KUL HUR SO RA KIM PYUNG KI LIM

We introduce the concepts of intuitionistic fuzzy k-ideals and intuitionistic fuzzy prime k-ideals of a semiring. And we investigate some properties of them.

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