Clustering is a standard approach in analysis of data and construction of separated similar groups. The most widely used robust soft clustering methods are fuzzy, rough and rough fuzzy clustering. The prominent feature of soft clustering leads to combine the rough and fuzzy sets. The Rough Fuzzy C-Means (RFCM) includes the lower and boundary estimation of rough sets, and fuzzy membership of fuz...

The problem of building recommender systems has attracted considerable attention in recent years. Collaborative Filtering (CF) is one of the most successful and widely used approaches in recommend system. Traditional collaborative filtering requires explicit user participation for providing his/her interest to the items. In this paper, we propose a novel collaborative filtering approach based o...

In this paper, an active learning method which can effectively select pairwise constraints during clustering procedure was presented. A novel semi-supervised text clustering algorithm was proposed, which employed an effective pairwise constraints selection method. As the samples on the fuzzy boundary are far away from the cluster center in the clustering procedure, they can be easily divided in...

Nowadays, geospatial information systems (GIS) are widely used to solve different spatial problems based on various types of fundamental data: spatial, temporal, attribute and topological relations. Topological relations are the most important part of GIS which distinguish it from the other kinds of information technologies. One of the important mechanisms for representing topological relations...

This paper proposes a hybrid boundary detection method for image based on a new modified level set method and a fuzzy model. It is applied to a boundary detection problem of coronary plaque. Level set method has been applied widely in image processing. It however does not work well for an intravascular ultrasound (IVUS) image because an image gradient, commonly used for calculating a speed func...

Feature subset selection is an essential preprocessing task in data mining. This paper presents a new method called Extended Fuzzy Relative Information Measure for Boundary Samples (EFRIMBS) for dealing with supervised feature subset selection. The proposed algorithm uses boundary samples instead of full set of samples. First, Discretization algorithms such as K-Means, Fuzzy C Means and Median ...

2. Obtain the gray-level gradient magnitude. 3. Derive the threshold surface by deforming the original image gray-level surface. 4. The threshold surface interpolation. 5. Segmentation based on the threshold surface. However, incomplete cells are still not detected reliably with this method. Double counting is sometimes occurred. In this paper, a Fuzzy Edge Detection Method is proposed. It is b...

Abstract The boundary layer approach is the most popular method to reduce the chattering phenomenon in sliding mode control (SMC) for uncertain nonlinear systems. This paper applies the fuzzy sliding mode structure based on the boundary layer theory which is used as speed controller of an indirect field-oriented control (IFOC) of an induction motor (IM) drive. A fuzzy inference system is assign...

This paper presents the necessary optimality conditions of Euler–Lagrange type for variational problems with natural boundary conditions and problems with holonomic constraints where the fuzzy fractional derivative is described in the combined Caputo sense. The new results are illustrated by computing the extremals of two fuzzy variational problems. AMS subject classifications: 65D10, 92C45