TSK fuzzy system, wavelet neural network and genetic algorithm used as an optimization process to obtain optimal values of parameters of translation, dilation and weights for the WNN and parameters of the Gaussian membership functions of the fuzzy inference
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چکیده
This paper presents a genetic algorithm based approach for designing fuzzy wavelet neural network (FWNN) and its application for control of dynamic plants. The structure of the proposed Fuzzy WNN consists of combination of two network structure. Upper side contains wavelet neural networks and down side contains network structure of the fuzzy inference system. A simple genetic algorithm is applied to train the parameters of the whole network structure. This approach is tested for the control of two dynamic plants commonly used in the literature.
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