Santos, HelidaPereira Dimuro, GraçalizBedregal, BenjaminPaiva, RuiLucca, GiancarloMoura, BrunoCruz, AndersonBustince Sola, Humberto2024-10-072024-10-072023Santos, H., Dimuro, G. P., Bedregal, B., Paiva, R., Asmus, T., Lucca, G., Moura, B., Cruz, A., Bustince, H. (2023) Additively Generated (a,b)-implication functions*. In IEEE International Conference on Fuzzy Systems, 2023 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1-5). IEEE. https://doi.org/10.1109/FUZZ52849.2023.10309754.979-8-3503-3228-510.1109/FUZZ52849.2023.10309754https://academica-e.unavarra.es/handle/2454/52033Some problems involving classification through neural networks are known to use inputs out of the scope of the unit interval. Therefore, defining operations on arbitrary closed real intervals may be an interesting strategy to tackle this issue and enhance those application environments. In this paper we follow the ideas already discussed in the literature regarding (a,b)-fusion functions, and (a,b)-negations, to provide a new way to construct implication functions. The main idea is to construct an operator using additively generated functions that preserve the properties required by implication functions.application/pdfeng© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work.(a, b)-negationsAdditive generatorsAggregation functionsImplication operatorsinfo:eu-repo/semantics/conferenceObject2024-10-07info:eu-repo/semantics/openAccess