Weighted Fuzzy Rules Based on Implicational Quantifiers
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-46775-2_3
Reference19 articles.
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2. Alcalá, R., Ramón Cano, J., Cordón, O., Herrera, F., Villar, P., Zwir, I.: Linguistic modeling with hierarchical systems of weighted linguistic rules. Int. J. Approx. Reasoning 32(2), 187–215 (2003). https://doi.org/10.1016/S0888-613X(02)00083-X, Soft Computing in Information Mining
3. Daňková, M.: Approximation of extensional fuzzy relations over residuated lattices. Fuzzy Sets Syst. 161(14), 1973–1991 (2010)
4. delaOssa, L., Gámez, J.A., Puerta, J.M.: Learning weighted linguistic fuzzy rules by using specifically-tailored hybrid estimation of distribution algorithms. Int. J. Approx. Reasoning 50(3), 541–560 (2009). https://doi.org/10.1016/j.ijar.2008.11.003, Special Section on Bayesian Modelling
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