In many data mining processes, neighborhood operators play an important role as they are generalizations of equivalence classes which were used in the original rough set model of Pawlak. In this article, we introduce the notion of fuzzy neighborhood system of an object based on a given fuzzy covering, as well as the notion of the fuzzy minimal and maximal descriptions of an object. Moreover, we...

For the problem of change detection it is difficult to have sufficient amount of ground truth information that is needed in supervised learning. On the contrary it is easy to identify a few labeled patterns by the experts. In this situation to avoid wastage of available information semi-supervision is suggestible to enhance the performance of unsupervised ones. Here we present the fuzzy cluster...

Methods like DBSCAN are widely used in the analysis of spatial data. These methods are based on the neighborhood relations which use distance between points. However, these neighborhood relations consider to have at least a certain number of neighbors within a definite boundary. In this proposed work such a neighborhood analysis is done by using the benefits of fuzzy sets theory. Usage of fuzzy...

In this paper, we introduce new definitions of L-fuzzy neighborhood systems, L-fuzzy interior operators and L-fuzzy closure operators. Three characterizations of the category L-FTOP of L-fuzzy topological spaces and their L-fuzzy continuous mappings are presented by means of the category L-FNS of L-fuzzy neighborhood spaces and their continuous mappings, the category L-FIS of L-fuzzy interior s...

Keywords: Double fuzzy topology Double neighborhood systems Double fuzzy preproximity Double fuzzy closure space a b s t r a c t In this paper, we introduce the notions of double neighborhood systems and double fuzzy preproximity in double fuzzy topological spaces. We used double neighborhoods to study the initial structure of double fuzzy topological spaces, and the joins between them and the ...

Rough set theory has been extensively discussed in machine learning and pattern recognition. It provides us another important theoretical tool for feature selection. In this paper, we construct a novel rough set model for feature subset selection. First, we define the fuzzy decision of a sample by using the concept of fuzzy neighborhood. A parameterized fuzzy relation is introduced to character...

A Fuzzy Adaptive Neighborhood Search for Function Optimization David A. Pelta Armando Blanco Jose-L. Verdegay Depto. de Ciencias de la Computaci6n e Inteiigencia Artificial. Universidad de Granada, Granada, Spain {dpelta,armando ,verdegay}@ugr . es Neighborhood based search algorithms have been applied with success in the optimization field. In this work, a Fuzzy Adaptive Neighborhood Search al...