Abstract
A system input-output response is modeled using a knowledge-based method of signal processing known as neuro-fuzzy logic. The paper presents a new method of the fuzzy model parameters tunning. Fuzzy model tuning procedures based on an evolutionary algorithm are also given. As an example, the analysis of the membership function kind is carried out for the fuzzy modeling of parameters, which are necessary to describe the state of a pressure vessel with water-steam mixture during accidental depressurizations.
This work was supported by the EU FP5 project DAMADICS and in part by the State Committee for Scientific Research in Poland (KBN)
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Pieczyński, A., Obuchowicz, A. (2004). Application of the General Gaussian Membership Function for the Fuzzy Model Parameters Tunning. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_50
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DOI: https://doi.org/10.1007/978-3-540-24844-6_50
Publisher Name: Springer, Berlin, Heidelberg
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