BUSCADOR RECOLECTA

We study a structural functional equation that is directly related to the pointwise aggregation of a finite number of maps from a given nonempty set into another. First we establish links between pointwise aggregation and invariance properties. Then, paying attention to the particular case of aggregation operators of a finite number of real-valued functions, we characterize several special kinds of aggregation operators as strictly monotone modifications of projections. As a case study, we introduce a first approach of type-2fuzzy sets via fusion operators. We develop some applications and possible uses related to the analysis of properties of social evaluation functionals in social choice, showing that those functionals can actually be described by using methods that derive from this setting., This work has been supported by the research projects ECO2012-34828,
MTM2012-37894-C02-02, MTM2015-63608-P, TIN2013-47605-P, TIN2011-29520 (Spain) and the Research Services of the Public University of Navarre.

In this work we introduce the notion of preaggregation
function. Such a function satisfies the same boundary
conditions as an aggregation function, but, instead of requiring
monotonicity, only monotonicity along some fixed direction (directional
monotonicity) is required. We present some examples
of such functions. We propose three different methods to build
pre-aggregation functions. We experimentally show that in fuzzy
rule-based classification systems, when we use one of these
methods, namely, the one based on the use of the Choquet
integral replacing the product by other aggregation functions,
if we consider the minimum or the Hamacher product t-norms
for such construction, we improve the results obtained when
applying the fuzzy reasoning methods obtained using two classical
averaging operators like the maximum and the Choquet integral., This work was supported in part by the Spanish Ministry of Science
and Technology under projects TIN2008-06681-C06-01, TIN2010-
15055, TIN2013-40765-P, TIN2011-29520.

In this paper we present a new fuzzy reasoning method in which the Choquet
integral is used as aggregation function. In this manner, we can take into account the
interaction among the rules of the system. For this reason, we consider several fuzzy
measures, since it is a key point on the subsequent success of the Choquet integral, and
we apply the new method with the same fuzzy measure for all the classes. However, the
relationship among the set of rules of each class can be different and therefore the best
fuzzy measure can change depending on the class. Consequently, we propose a learning
method by means of a genetic algorithm in which the most suitable fuzzy measure for
each class is computed. From the obtained results it is shown that our new proposal
allows the performance of the classical fuzzy reasoning methods of the winning rule and
additive combination to be enhanced whenever the fuzzy measure is appropriate for the
tackled problem., This work was partially supported by the Spanish Ministry of Science and Technology under projects
TIN2010-15055 and TIN2011-29520.

In this paper we present a comparison study between different
aggregation functions for the combination of RGB color channels in stereo
matching problem. We introduce color information from images to the
stereo matching algorithm by aggregating the similarities of the RGB
channels which are calculated independently. We compare the accuracy
of different stereo matching algorithms and aggregation functions. We
show experimentally that the best function depends on the stereo matching
algorithm considered, but the dual of the geometric mean excels as the most
robust aggregation., This paper has been partially supported by the National Science Foundation of Spain, Reference
TIN2010-15055, TIN2011-29520 and the Research Services of the Universidad Publica de
Navarra.