in this paper, the concept of countably near ps-compactness inl-topological spaces is introduced, where l is a completely distributive latticewith an order-reversing involution. countably near ps-compactness is definedfor arbitrary l-subsets and some of its fundamental properties are studied.

This note studies the relationship between Hutton's quasi-uniformities and Shi's quasi-uniformities. It is shown that when $L$ satisfies``multiple choice principle" for co-prime elements, the category of Hutton's quasi-uniform spaces is a bireflective full subcategory of the category of Shi's quasi-uniform spaces. Especially, if the remote-neighborhood mapping defined by Shi preserves arbitrary...

in this paper, we study some properties of the near sr-compactnessin l-topological spaces, where l is a fuzzy lattice. the near sr-compactness isa kind of compactness between lowen’s fuzzy compactness and sr-compactness,and it preserves desirable properties of compactness in general topologicalspaces.

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...

In present days remote sensing is most used application in many sectors. This remote sensing uses different images like multispectral, hyper spectral or ultra spectral. The remote sensing image classification is one of the significant method to classify image. In this state we classify the maximum likelihood classification with fuzzy logic. In this we experimenting fuzzy logic like spatial, spe...

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...

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 primary objective of the current study is to produce karstification potentiality maps in northeast of khuzestan province, iran, using both fuzzy logic and ahp models as an additional tool in hydrogeological research. geographic information systems (gis) and remote sensing (rs) are used to create two maps depicting the development of the karstification, consisting of five classes, showing th...

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...