A new family of aggregation functions for intervals
Fecha
2024Autor
Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión publicada / Argitaratu den bertsioa
Identificador del proyecto
Impacto
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10.1007/s40314-023-02525-1
Resumen
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 for the same element/object. In this contribution we assume that the opinions are not given in form of isolated values, but intervals. We depart from two “classical” aggregation ...
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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 for the same element/object. In this contribution we assume that the opinions are not given in form of isolated values, but intervals. We depart from two “classical” aggregation functions and define a new operator for aggregating intervals based on the two original operators. We study under what circumstances this new function is well defined and we provide a general characterization for monotonicity. We also study the behaviour of this operator when the departing functions are the most common aggregation operators. We also provide an illustrative example demonstrating the practical application of the theoretical contribution to ensemble deep learning models. [--]
Materias
Aggregation function,
Injectivity,
Intervals,
Monotonicity
Editor
Springer
Publicado en
Computational and Applied Mathematics (2024), 43(17)
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Versión del editor
Entidades Financiadoras
Authors would like to thank for the support of the Spanish Ministry of Science and Innovation projects PID2022-139886NB-I00 (S. Diaz-Vazquez, E. Torres-Manzanera, N. Rico, I. Diaz and S. Montes) and Ministerio de Educación y Formación Profesional PID2022-136627NB-I00 (I. Rodriguez-Martinez and H. Bustince).