Abstract
In this paper we presented a general solution to compose rough-neuro-fuzzy architectures. The fuzzy system in the case of missing features is derived without the assumption that used fuzzy implication is monotonic. The proposed solution is also suitable for the monotonic fuzzy implications satisfying Fodor’s lemma. The architecture based on the Zadeh and Willmott fuzzy implications is derived as the special case of the proposed general solution.
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Nowicki, R. (2004). Rough Sets in the Neuro-Fuzzy Architectures Based on Non-monotonic Fuzzy Implications. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_77
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DOI: https://doi.org/10.1007/978-3-540-24844-6_77
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