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A self-organized fuzzy neural network approach for rule generation of fuzzy logic systems

Communications in Computer and Information Science (2013) 375 25-30
DOI: 10.1007/978-3-642-39678-6_5
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Abstract

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. © Springer-Verlag Berlin Heidelberg 2013.

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Figueroa-García, J. C., Ochoa-Rey, C., & Avellaneda-González, J. (2013). A self-organized fuzzy neural network approach for rule generation of fuzzy logic systems. In Communications in Computer and Information Science (Vol. 375, pp. 25–30). Springer Verlag. https://doi.org/10.1007/978-3-642-39678-6_5

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