d-XC integrals: on the generalization of the expanded form of the Choquet integral by restricted dissimilarity functions and their applications

Autor: Jonata Wieczynski, Javier Fumanal-Idocin, Giancarlo Lucca, Eduardo Nunes Borges, Tiago da Cruz Asmus, Leonardo Ramos Emmendorfer, Humberto Bustince, Gracaliz Pereira Dimuro
Přispěvatelé: Universidad Pública de Navarra. Departamento de Automática y Computación, Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas, Nafarroako Unibertsitate Publikoa. Automatika eta Konputazioa Saila, Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematikak Saila
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Popis: Restricted dissimilarity functions (RDFs) were introduced to overcome problems resulting from the adoption of the standard difference. Based on those RDFs, Bustince et al. introduced a generalization of the Choquet integral (CI), called d-Choquet integral, where the authors replaced standard differences with RDFs, providing interesting theoretical results. Motivated by such worthy properties, joint with the excellent performance in applications of other generalizations of the CI (using its expanded form, mainly), this paper introduces a generalization of the expanded form of the standard Choquet integral (X-CI) based on RDFs, which we named d-XC integrals. We present not only relevant theoretical results but also two examples of applications. We apply d-XC integrals in two problems in decision making, namely a supplier selection problem (which is a multi-criteria decision making problem) and a classification problem in signal processing, based on motor-imagery brain-computer interface (MI-BCI). We found that two d-XC integrals provided better results when compared to the original CI in the supplier selection problem. Besides that, one of the d-XC integrals performed better than any previous MI-BCI results obtained with this framework in the considered signal processing problem. This work was supported by Navarra de Servicios y Tecnologías, S.A. (NASERTIC), FAPERGS-Brazil (19/2551-0001279-9, 19/2551-0001660), CNPq-Brazil (301618/2019-4, 305805/2021-5), the Spanish Ministry of Science and Technology (TIN2016-77356-P, PID2019-108392GB-I00 (MCIN/AEI/10.13039/501100011033)).
Databáze: OpenAIRE