A Self-Organized Fuzzy Neural Network Approach for Rule Generation of Fuzzy Logic Systems

This paper shows an algorithm for creating fuzzy logic systems from data by synchronizing its fuzzy sets and rules using a novel neuro fuzzy approach to generate rules and fuzzy sets from analyzing input data. A volatile time series example is solved and analyzed using the residuals of the model.

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