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Some preference involved aggregation models for basic uncertain information using uncertainty transformation
(IOS Press, 2020)
Artículo / Artikulua,
In decision making, very often the data collected are with different extents of uncertainty. The recently introduced concept, Basic Uncertain Information (BUI), serves as one ideal information representation to well model ...
Dissimilarity based choquet integrals
(Springer, 2020)
info:eu-repo/semantics/conferenceObject,
In this paper, in order to generalize the Choquet integral, we replace the difference between inputs in its definition by a restricted dissimilarity function and refer to the obtained function as d-Choquet integral. For ...
Non-symmetric over-time pooling using pseudo-grouping functions for convolutional neural networks
(Elsevier, 2024)
Artículo / Artikulua,
Convolutional Neural Networks (CNNs) are a family of networks that have become state-of-the-art in several fields of artificial intelligence due to their ability to extract spatial features. In the context of natural ...
A generalization of the Sugeno integral to aggregate interval-valued data: an application to brain computer interface and social network analysis
(Elsevier, 2022)
Artículo / Artikulua,
Intervals are a popular way to represent the uncertainty related to data, in which we express the vagueness of each observation as the width of the interval. However, when using intervals for this purpose, we need to use ...
Some properties of implications via aggregation functions and overlap functions
(Taylor & Francis, 2014)
Artículo / Artikulua,
In this work, using the identification between implication operators and aggregation functions, we study
the implication operators that are recovered from overlap functions. In particular, we focus in which
properties ...
A framework for generalized monotonicity of fusion functions
(Elsevier, 2023)
Artículo / Artikulua,
The relaxation of the property of monotonicity is a trend in the theory of aggregation and fusion functions and several generalized forms of monotonicity have been introduced, most of which are based on the notion of ...
New classes of the moderate deviation functions
(Springer Nature, 2021)
Contribución a congreso / Biltzarrerako ekarpena,
At present, in the field of aggregation of various input values, attention is focused on the construction of aggregation functions using other functions that can affect the resulting aggregated value. This resulting value ...
Affine construction methodology of aggregation functions
(Elsevier, 2020)
info:eu-repo/semantics/article,
Aggregation functions have attracted much attention in recent times because of its potential use in many areas such us data fusion and decision making. In practice, most of the aggregation functions that scientists use in ...
Mixture functions and their monotonicity
(Elsevier, 2019)
info:eu-repo/semantics/article,
We consider mixture functions, which are a type of weighted averages for which the corresponding weights are calculated by means of appropriate continuous functions of their inputs. In general, these mixture function need ...
A new family of aggregation functions for intervals
(Springer, 2024)
Artículo / Artikulua,
Aggregation operators are unvaluable tools when different pieces of information have to be taken into account with respect to the same object. They allow to obtain a unique outcome when different evaluations are available ...