Spatial relations play important role in computer vision, scene analysis, geographic information systems (GIS) and content based image retrieval. Analyzing spatial relations by Force histogram was introduced by Miyajima et al [10] and largely developed by Matsakis [12] who used a quantitative representation of relative position between 2D objects. Fuzzy Allen relations are used to define the fu...

and Applied Analysis 3 2.1. Fuzzy Numbers In this section, we give certain essential concepts of fuzzy numbers and their basic properties. For further information see 2, 3 . A fuzzy set à on a set X is a function à : X → 0, 1 . Generally, the symbol μà is used for the function à and it is said that the fuzzy set à is characterized by itsmembership function μà : X → 0, 1 which associates with ea...

Paraconsistent intuitionistic fuzzy set is an extension of intuitionistic fuzzy set or interval-valued fuzzy set. It relaxes the requirement that t + f ≤ 1, where t is grade of truth-membership and f is grade of false-membership. In paraconsistent intuitionistic fuzzy set, t, f ∈ [0, 1], 0 ≤ t + f ≤ 2. In this paper, we present a generalization of the relational model of data based on paraconsi...

Topological relations are one of the most fundamental properties between spatial objects. The topological relations between crisp spatial objects have been well identified. However how to formalise the topological relations between fuzzy regions needs more investigation. The paper starts from introduction of boundaries defined in the fuzzy topological space. By use of a definition formally equi...

Preference analysis is an important task in multi-criteria decision making. The rough set theory has been successfully extended to deal with preference analysis by replacing equivalence relations with dominance relations. The existing studies involving preference relations cannot capture the uncertainty presented in numerical and fuzzy criteria. In this paper, we introduce a method to extract f...

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...

Using the concept of (K,L)-eigenvector, we investigate structure max-min eigenspace associated with a given eigenvalue matrix in algebra (also known as fuzzy algebra). In our approach, is split into several regions according to order relations between and components x. The resulting theory (K,L)-eigenvectors, being based on fundamental results Gondran Minoux, allows describe whole explicitly mo...

Abstract. Studied is the issue of similarity relations in fuzzy concept lattices. Fuzzy concepts and fuzzy concept lattices represent a formal approach to the modeling of non-sharp (fuzzy) concepts and conceptual structures in the sense of traditional (PortRoyal) logic. Applications of concept lattices are in representation of conceptual knowledge and in conceptual analysis of (fuzzy) data. Sim...

small polygroups are multi-valued systems that satisfy group-likeaxioms. using the notion of “belonging ($epsilon$)” and “quasi-coincidence (q)” offuzzy points with fuzzy sets, the concept of ($epsilon$, $epsilon$ $vee$ q)-fuzzy subpolygroups isintroduced. the study of ($epsilon$, $epsilon$ $vee$ q)-fuzzy normal subpolygroups of a polygroupare dealt with. characterization and some of the fundam...

For sequences of fuzzy numbers, Nanda 1 studied the sequences of fuzzy numbers and showed that the set of all convergent sequences of fuzzy numbers forms a complete metric space. Kwon 2 introduced the definition of strongly p-Cesàro summability of sequences of fuzzy numbers. Savaş 3 introduced and discussed double convergent sequences of fuzzy numbers and showed that the set of all double conve...