Abstract
One of the widest application areas for fuzzy logic is represented by processes control in the industrial environment. In such a kind of applications the main difficulty lies in the process modelling by means of Fuzzy Logic data structures. Up to now, the user only had the possibility to “manually” define the rules and membership functions, in order to model the process. This operation is quite difficult and requires a long time to be performed. In this paper a Neuro-Fuzzy system is proposed. The main innovation of this tool with respect to the majoritiy of the other fuzzy tools is represented by its capability to automatically perform the process modelling. The structure and learning algorithm of the implemented neural networks will be described and an application example will be proposed in order to allow the reader to understand the usefulness of the system.
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© 1994 Springer-Verlag Berlin Heidelberg
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Gianferrara, P., Poluzzi, R., Serina, N. (1994). A Neuro-Fuzzy Approach for Process Modelling. In: Reusch, B. (eds) Fuzzy Logik. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79386-8_47
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DOI: https://doi.org/10.1007/978-3-642-79386-8_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-58649-4
Online ISBN: 978-3-642-79386-8
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