28,965 research outputs found
Multi-criteria decision making with linguistic labels: a comparison of two methodologies applied to energy planning
This paper compares two multi-criteria decision making (MCDM) approaches based on linguistic label assessment. The first approach consists of a modified fuzzy TOPSIS methodology introduced by Kaya and Kahraman in 2011. The
second approach, introduced by Agell et al. in 2012, is based on qualitative reasoning techniques for ranking multi-attribute alternatives in group decision-making with linguistic labels. Both approaches are applied to a case of assessment and selection of the most suitable types of energy in a geographical area.Peer ReviewedPostprint (published version
Fuzzy Recommendations in Marketing Campaigns
The population in Sweden is growing rapidly due to immigration. In this
light, the issue of infrastructure upgrades to provide telecommunication
services is of importance. New antennas can be installed at hot spots of user
demand, which will require an investment, and/or the clientele expansion can be
carried out in a planned manner to promote the exploitation of the
infrastructure in the less loaded geographical zones. In this paper, we explore
the second alternative. Informally speaking, the term Infrastructure-Stressing
describes a user who stays in the zones of high demand, which are prone to
produce service failures, if further loaded. We have studied the
Infrastructure-Stressing population in the light of their correlation with
geo-demographic segments. This is motivated by the fact that specific
geo-demographic segments can be targeted via marketing campaigns. Fuzzy logic
is applied to create an interface between big data, numeric methods for
processing big data and a manager.Comment: conferenc
Introduction
There has been little overt discussion of the experimental philosophy of logic or mathematics. So it may be tempting to assume that application of the methods of experimental philosophy to these areas is impractical or unavailing. This assumption is undercut by three trends in recent research: a renewed interest in historical antecedents of experimental philosophy in philosophical logic; a “practice turn” in the philosophies of mathematics and logic; and philosophical interest in a substantial body of work in adjacent disciplines, such as the psychology of reasoning and mathematics education. This introduction offers a snapshot of each trend and addresses how they intersect with some of the standard criticisms of experimental philosophy. It also briefly summarizes the specific contribution of the other chapters of this book
An introduction to DSmT
The management and combination of uncertain, imprecise, fuzzy and even
paradoxical or high conflicting sources of information has always been, and
still remains today, of primal importance for the development of reliable
modern information systems involving artificial reasoning. In this
introduction, we present a survey of our recent theory of plausible and
paradoxical reasoning, known as Dezert-Smarandache Theory (DSmT), developed for
dealing with imprecise, uncertain and conflicting sources of information. We
focus our presentation on the foundations of DSmT and on its most important
rules of combination, rather than on browsing specific applications of DSmT
available in literature. Several simple examples are given throughout this
presentation to show the efficiency and the generality of this new approach
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