Rough Standard Neutrosophic Sets: an Application on standard Neutrosophic Information Systems

A rough fuzzy set is the result of approximation of a fuzzy set with respect to a crisp approximation space. It is mathematical tool for the knowledge discovery in the fuzzy information systems. In this paper, we introduce the concepts of rough standard neutrosophic sets, standard neutrosophic information system and give the knowledge discovery on standard neutrosophic information system based on rough standard neutrosophic sets

Sublinear-Space Bounded-Delay Enumeration for Massive Network Analytics: Maximal Cliques

Due to the sheer size of real-world networks, delay and space become quite relevant measures for the cost of enumeration in network analytics. This paper presents efficient algorithms for listing maximum cliques in networks, providing the first sublinear-space bounds with guaranteed delay per enumerated clique, thus comparing favorably with the known literature

Rough Standard Neutrosophic Sets: An Application on Standard Neutrosophic Information Systems

A rough fuzzy set is the result of the approximation of a fuzzy set with respect to a crisp approximation space. It is a mathematical tool for the knowledge discovery in the fuzzy information systems. In this paper, we introduce the concepts of rough standard neutrosophic sets and standard neutrosophic information system, and give some results of the knowledge discovery on standard neutrosophic information system based on rough standard neutrosophic sets

General set approximation and its logical applications *

Abstract To approximate sets a number of theories have appeared for the last decades. Starting up from some general theoretical pre-conditions the authors give a set of minimum requirements for the lower and upper approximations and define general partial approximation spaces. Then, these spaces are applied in logical investigations. The main question is what happens in the semantics of the first-order logic when the approximations of sets as semantic values of predicate parameters are used instead of sets as their total interpretations. On the basis of defined partial interpretations, logical laws relying on the defined general set-theoretical framework of set approximation are investigated

Rough picture fuzzy set and picture fuzzy topologies

Approximation of a picture fuzzy set on a crisp approximation space gives a rough picture fuzzy set. In this paper, the concept of a rough picture set is introduced, besides, we also investigate some topological structures of a rough picture fuzzy set are investigated, such are lower and upper rough picture fuzzy approximation operators

Measuring the nearness of layered flow graphs: Application to Content Based Image Retrieval

Preprint version.Rough set based flow graphs represent the flow of information for a given data set where branches of these could be constructed as decision rules. However, in the recent years, the concept of flow graphs has been applied to perceptual systems (also called perceptual flow graphs) where they play a vital role in determining the nearness among disjoint sets of perceptual objects. Perceptual flow graphs were first introduced to represent and reason about sufficiently near visual points in images. In this paper, we have given a practical implementation of flow graphs induced by a perceptual system, defined with respect to digital images, to perform Content-Based Image Retrieval(CBIR). Results are generated using the SIMPLicity dataset, and our results are compared with the near-set based tolerance nearness measure(tNM)."This research has been supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) discovery grants 194376 and 418413.