The original definition of a topological space given by Hausdorff used neighborhood systems. Lattice-valued maps appear in this context when you identify a topology with a monoid in the Kleisli category of the filter monad on SET. H?hle’s notion of a lattice-valued topology [2] uses the same idea and it’s inspired in the classical lattice-valued topologies. Ltopological spaces are motivated by ...

More recently Turkey has witnessed fast housing development and real estate sector growth because of the mortgage preparations. With this development, property location quality has been considered important for selecting and paying them. This study uses a data set of new single family housing units in Kocaeli University Campus Area. By using 4 location quality criteria, 27 single family housing...

The purpose of this paper is to introduce Shi’s (quasi-)uniformity structure in the context of fuzzy soft sets. We define the notion of a fuzzy soft (quasi-)uniformity in the sense of Shi. We give the relations between a fuzzy soft (quasi-)uniformity and a fuzzy soft cotopology. Also, we investigate the relations between fuzzy soft remote neighborhood structures which are generated by a given f...

The competitive fuzzy classifier operates on the set of four features extracted from the 3x3 neighborhood of each pixel. These features are the magnitudes of differences between that pixel and its neighboring pixels on four directions. They are input into the competitive fuzzy classifier inputs that connect to five fuzzy set membership functions that represent “white background” or one of the f...

This paper presents a novel approach to the weak classifier selection based on the GentleBoost framework. We include explicitly the notion of neighborhood in one of the most common weak learner in boosting, the decision stumps. The availability of neighboring points adds a new parameter to the decision stump, the feature set (i.e. neighborhood), and turns the single branch selection of the deci...

Considering a frame L, we introduce the notions of stratified L-semi-topological neighborhood group, stratified L-quasi-topological neighborhood group, and stratified L-quasi-bi-topological neighborhood group. In so doing, we look at the notion of stratified L-right (left) semi-topological neighborhood group, provide some basic facts, and present a construction of a stratified L-right semi-topo...

The difference of Fuzzy Joint Points (FJP) algorithm from other neighborhood-based clustering algorithms is that it uses the concept of fuzzy neighborhood when computing the neighborhood relations. Among the proposed methods, none of them is perfect for all aspects of clustering requirements. Although FJP algorithm has superiority by its advantages of robustness and optimal determination of the...

The aim of this paper is to introduce and study the fuzzy neighborhood, the limit fuzzy number, the convergent fuzzy sequence, the bounded fuzzy sequence, and the Cauchy fuzzy sequence on the base which is adopted by Abdul Hameed every real number r is replaced by a fuzzy number r either triangular fuzzy number or singleton fuzzy set fuzzy point . And then, we will consider that some results re...

In this paper, the concepts of $L$-concave structures, concave $L$-interior operators and concave $L$-neighborhood systems are introduced. It is shown that the category of $L$-concave spaces and the category of concave $L$-interior spaces are isomorphic, and they are both isomorphic to the category of concave $L$-neighborhood systems whenever $L$ is a completely distributive lattice. Also, it i...