Juan Tinguaro Rodríguez

A fuzzy and bipolar approach to preference modeling with application to need and desire

Fuzziness and bipolarity allow representing human knowledge, taking into account the gradual and the dialectic properties of language, focusing on the meaning of concepts. Under this cognitive and linguistic approach, we explore preference relations, examining their semantic decomposition through fuzzy preference structures and the specification of meaningful opposites. In particular, we introduce the Preference-Aversion (P-A) model, which allows analyzing, under an independent aggregation methodology, the possible gains and losses, like pros and cons, towards a given set of alternatives. As an attractive feature of this proposal, we show that the P-A model allows distinguishing between need and desire, contrary to common preference models where both notions are indistinguishable.

Classifying image analysis techniques from their output

In this paper we discuss some main image processing techniques in order to propose a classification based upon the output these methods provide. Because despite a particular image analysis technique can be supervised or unsupervised, and can allow or not the existence of fuzzy information at some stage, each technique has been usually designed to focus on a specific objective, and their outputs are in fact different according to each objective. Thus, they are in fact different methods. But due to the essential relationship between them they are quite often confused. In particular, this paper pursues a clarification of the differences between image segmentation and edge detection, among other image processing techniques.

Formal Specification and Implementation of Computational aggregation functions

This paper recalls some criticisms to the currently-in-use definition of aggregation function, concerning, firstly, the lack of conditions that guarantee the conceptual harmonization of the sequence of operators and, second, the possibility of the so defined functions being not practically implementable. In order to address such criticisms, an alternative definition was proposed in a previous work from a computational approach. Here, we go one step further by giving a definition of the formal specification of an aggregation function. This enables to introduce a first classification of aggregation rules.

Intelligent Decision-Making Models for Disaster Management

ABSTRACT Providing emergency relief to the victims of natural disasters is a hugely complex process fraught with many challenging aspects: multiple uncertainties, little reliable information, scarcity of resources, a variety of involved entities, and so on. Nowadays there is a lot of information that could be used to improve decision-making in disaster management, but usually it is not available at the right moment, in the right way, or it is partially known or vague. In this article we analyze the decision-making process for disaster management from the general view of intelligent decision-making to the specific characteristics of this context. This specificity deals with a new kind of logistics, and it is shown how this humanitarian logistics, specifically designed with the aim of alleviating suffering of vulnerable people, is a growing new research area to develop new decision aid models for disaster management, identifying new and relevant differences with other types of logistics. To illustrate these claims, two models are introduced, one for assessment of consequences in the earlier stage after a disaster (focused on the unknown, one of the main characteristics in disaster management), and another one for last mile distribution of humanitarian aid (focused on the multicriteria nature of decision-making on disaster management).

A New concept of of fuzzy image segmentation

A crisp image segmentation can be characterized in terms of the set of edges that separates the adjacent regions of the segmentation. Based on these edges, an alternative way to define a fuzzy image segmentation is introduced in this paper. In this sense, the notion of fuzzy image segmentation is characterized by means of a fuzzy set over the set of edges, which could in this way be understood as the fuzzy boundary of the image. Also, an algorithm to construct this fuzzy boundary is provided based on the relations that exist

A decision support tool for humanitarian operations in natural disaster relief

In this paper we present a decision support system for primary action of international organizations devoted to natural disaster relief In particular, we pretend to build up an expert system that taking into account past experiences will help decision makers, mainly non-governmental organizations, to start or not an operation, depending on the place and the very first information about a possible natural disaster. The relevance of this issue is extreme, since such a decision must be taken as soon as possible.

Bipolarity in social sciences and mathematics

The polarity of concepts and the dialectic process by which its meaning emerges has been subject of interest since the ancient Greeks. Recently, the term Bipolarity has been used in social and mathematical sciences, referring to the measurement of the meaning of concepts. It is claimed that the measuring process has to consider at least an associated pair of meaningful opposites, such that some type of structure is used to analyze the aspect of reality that is being modeled. From this point of view, we take a quick overview on the genealogy of Bipolarity, discussing some ideas about the nature of negative knowledge, and how it has been examined recently, and not so recently, by the mathematical community.

A new view on the relationships between interval valured and intuitionistic fuzzy sets

This paper proposes a novel approach to analyze the relationship between interval valued fuzzy sets (IVFS) and Atanassov’s intuitionistic fuzzy sets (AIFS), based on the recently introduced notion of paired structure. It is suggested that the different semantics of IVFS and AIFS, with respect to their particular purposes as extensions of fuzzy sets, can be formally recovered and separated in the framework of paired structures, pointing out that both models actually provide a quite different representational performance.

Types of bipolarity and bipolar structures

In this paper we revise the three types of bipolarity recently proposed by Dubois and Prade, focussing on how the basic structure is being built up. In this way we can clarify key differences between them, and formalize to what extent some structures can be considered bipolar extensions. In particular, We stress the existence of alternative different concepts underlying their type II polarity, which may lead to different 3-valued structures, and the essential complexity underlying their type III polarity.