Abstract
The neuro-fuzzy systems (with possible supportive usage of genetic algorithms) presented and discussed in Chapters 6, 7 and 8 implement one of two general ideas of combining artificial neural networks and fuzzy sets (see discussion in Chapter 5). This idea consists in using artificial neural networks within the framework of fuzzy modelling and designing fuzzy systems. This approach aims at providing fuzzy systems with tools for the automatic tuning of their parameters, but without changing their general functional structure. In particular, the fuzzy rule base is still present in these systems and they are interpretable in the domain context (they are said to be transparent).
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© 2002 Springer-Verlag Berlin Heidelberg
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Gorzałczany, M.B. (2002). Fuzzy neural network for system modelling and control. In: Computational Intelligence Systems and Applications. Studies in Fuzziness and Soft Computing, vol 86. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1801-7_9
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DOI: https://doi.org/10.1007/978-3-7908-1801-7_9
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-662-00334-3
Online ISBN: 978-3-7908-1801-7
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