Abstract
Building in of fuzzy logic into the neural network structure and application of the back-propagation learning algorithm allows construction of the neuro fuzzy system (NFS). The performance of this approach in calibration of the non-linear systems was evaluated using simulated and experimental data sets. A comparison of the obtained results with an outcome of several other approaches, i.e., neural networks, and principal component analysis-neural networks, was performed.
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