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In this paper, a new classification method based on LVQ neural networks and Fuzzy Logic is presented. This new fuzzy LVQ method (FuzzLVQ) mainly focuses on distances between the input vector and the cluster centers, randomly generated, thus the fuzzy system in the FuzzLVQ method is used to determine the shortest distance, and with this information, the cluster center can be approached to input vector...
In this paper we describe an evolutionary method for the optimization of type-2 fuzzy systems based on the level of uncertainty. The proposed evolutionary method produces the best fuzzy inference systems (based on the memberships functions) for particular applications. The optimization of membership functions of the type-2 fuzzy systems is based on the level of uncertainty considering three different...
We describe in this paper a new approach for automated mathematical modelling and simulation of robotic dynamic systems using fuzzy logic techniques, genetic algorithms and fractal theory. The new fuzzy-fractal-genetic approach combines soft computing techniques with mathematical methods for the domain of modelling and simulation of robotic systems. This domain is quite complex because robotic systems...
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