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Takagi-Sugeno (T-S) fuzzy system was merged into Hierarchical Hybrid Fuzzy-Neural Networks (HHFNN) and homogeneous linear function of input variables was employed in the THEN part of fuzzy rules of T-S fuzzy systems. A new training algorithm for this model was also proposed. The parameters consist of the coefficients of homogeneous linear functions and the weights and bias terms of upper neural network...
A new training algorithm for hierarchical hybrid fuzzy–neural networks (HHFNN) based on Gaussian membership function is proposed in this paper. This new algorithm adjusts the widths of Gaussian membership functions of the IF parts of fuzzy rules in the lower fuzzy sub-systems, and updates the weights and bias terms of the upper neural network by gradient-descent method. Two advantages of the proposed...
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