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Each rule consequent node sums the output of the layer 3 nodes, which see this layer 4 node as a consequence, to identify the degree of membership for the consequent part of the rule.
The consequent part comprises local models (linear functions).
Each rule in this FLC has an SMC or an SFC in the consequent part.
The backpropagation algorithm was used for the learning process of antecedent fuzzy beta parameters and the consequent part.
In addition, Recursive Least Square (RLS) algorithm is used to adjust the consequent part of the T S system.
In particular, we attempt at lyapunov constraining the consequent part of fuzzy rules in a fuzzy RL setup.
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It adapts their parameters in antecedent and consequent parts with any newly loaded sample.
Afterwards, the proposed fuzzy neural network quantifies the impacts of fuzzy rules on the consequent parts by fuzzy connections based on mutual subsethood.
In addition to these intuitive and experimental design efforts, consequent parts of the fuzzy rules are optimally (or near optimally) determined using the particle swarm optimization algorithm.
The structure of FWNN is based on the basis of fuzzy rules including wavelet functions in the consequent parts of rules.
For the NFS ARIMA, the focus is on the design of fuzzy If-Then rules, where ARIMA models are embedded in the consequent parts of If-Then rules.
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Justyna Jupowicz-Kozak
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