2026-07-072026-07-07http://salesiana.dossiersoluciones.com/handle/123456789/32684This article presents the Neo-Fuzzy-Neuron Modified by Kohonen Network (NFN-MK), an hybrid computational model that combines fuzzy system technique and artificial neural networks. Its main task consists in the automatic generation of membership functions, in particular, triangle forms, aiming a dynamic modeling of a system. The model is tested by simulating real systems, here represented by a nonlinear mathematical function. Comparison with the results obtained by traditional neural networks, and correlated studies of neurofuzzy systems applied in system identification area, shows that the NFN-MK model has a similar performance, despite its greater simplicity.6 pages, 6 figures, 5th Congress of Logic Applied to Technology (LAPTEC 2005) Himeji, Japan, April 2-6, 2005Neural and Evolutionary ComputingC.1.3; I.2.6text