Combining clusterings in the belief function framework

International audienceIn this paper, we propose a clustering ensemble method based on Dempster-Shafer Theory. In the first step, base partitions are generated by evidential clustering algorithms such as the evidential c-means or EVCLUS. Base credal partitions are then converted to their relational representations, which are combined by averaging. The combined relational representation is then made transitive using the theory of intuitionistic fuzzy relations. Finally, the consensus solution is obtained by minimizing an error function. Experiments with simulated and real datasets show the good performances of this method

Transitive Closure of Interval-valued Relations

This paper introduces some concepts of intervalvalued fuzzy relations and some of their properties: reflexivity, symmetry, T-transitivity, composition and locally reflexivity. It is also introduced the concept of T-transitive closure for an interval-valued fuzzy relation. An algorithm to compute the T-transitive closure of finite interval-valued relations, some properties and some examples are given.Peer ReviewedPostprint (published version

The notion of H-IFS -an approach for enhancing query capabilities in Oracle10g

Query answering requirements for a knowledge based treatment of user requests led us to introduce the concept of closure of an Intuitionistic fuzzy set over a universe that has a hierarchical structure. We introduce the automatic analysis of queries according to concepts defined as part of a knowledge based hierarchy in order to guide the query answering as part of an integrated database environment with the aid of hierarchical Intuitionistic fuzzy sets, H-IFS. In this paper based on the notion of H-IFS we propose an ad-hoc utility build on top of Oracle10g that allows us to enhance the query capabilities of by providing better and knowledgeable answers to user’s requests. The theoretical aspects as well the practical issues and achieved results are presented throughout the rest of the paper

The notion of H-IFS in data modelling

In this paper we revise the context of "value imprecision", as part of an knowledge-based environment We present our approach for including value imprecision as pan of a non-rigid hierarchical structures of organization. This led us to introduce the concept of closure of an Intuitionistic fuzzy set over a universe that has a hierarchical structure. Intuitively, in the closure of this Intuitionistic fuzzy set, the "kind of" relation is taken into account by propagating the degree associated wit an element to its sub-elements in the hierarchy. We introduce the automatic analysis according to concepts defined as part of a knowledge hierarchy in order to guide the query answering as part of an integrated database environment with the aid of hierarchical intuitionistic fuzzy sets

Related Study of Soft Set and Its Application A Review

Abstract In the present paper some literature related to soft sets are collected. The literature is motivated by Molodsov

Fuzzy algorithm applied to factors influencing competitiveness: A case study of Brazil and Peru through affinities theory

Innovation plays a crucial role in the economy of nations worldwide. In Latin America, countries foster competitiveness through public and private incentives to support innovation. Moreover, entrepreneurship incentives seek to improve countries’ performance, although factors such as low business growth rates and informality can compromise it. Despite the efforts, there are several difficulties in achieving competitiveness, and few studies in developing countries. Therefore, the article explores the relationship between the factors that influence competitiveness, especially the role of innovation and entrepreneurship in Brazil and Peru. The research uses quantitative-qualitative methodology through modeling and simulation and a case study. The authors use the Affinities Theory to verify the relationship between the indicators that make up the competitiveness landscape and its most significant and attractive factors, adapting the methodology established by the International Institute for Management Development (IMD) World Competitiveness ranking. As a result, this algorithm allows us to know the relationships between five factors of economic attractiveness and four competitiveness indicators. As its main contributions, the study advances the frontier of knowledge about innovation and entrepreneurship, as few studies explore competitiveness in developing countries. Also, it offers a detailed explanation of the application of this algorithm, allowing researchers to reproduce this methodology in other scenarios. Practically, it might support policymakers in formulating development strategies and stimuli for business competitiveness. In addition, academic and business leaders can strengthen university-business collaboration with applied research in innovation and entrepreneurship. One limitation would be the number of countries participating in the research. The authors suggest future lines of research.Project number 522RT0130 in Programa Ibero-americano de Ciências y Tecnologia para el Desarrolho (CYTED)info:eu-repo/semantics/publishedVersio

A Novel Rough Set Model in Generalized Single Valued Neutrosophic Approximation Spaces and Its Application

In this paper, we extend the rough set model on two different universes in intuitionistic fuzzy approximation spaces to a single-valued neutrosophic environment