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Content available A new approach to nonlinear modelling of dynamic systems based on fuzzy rules
Bartczuk Ł., Przybył A., Cpałka K.
International Journal of Applied Mathematics and Computer Science
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2016
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Vol. 26, no. 3
603--621
EN
For many practical weakly nonlinear systems we have their approximated linear model. Its parameters are known or can be determined by one of typical identification procedures. The model obtained using these methods well describes the main features of the system’s dynamics. However, usually it has a low accuracy, which can be a result of the omission of many secondary phenomena in its description. In this paper we propose a new approach to the modelling of weakly nonlinear dynamic systems. In this approach we assume that the model of the weakly nonlinear system is composed of two parts: a linear term and a separate nonlinear correction term. The elements of the correction term are described by fuzzy rules which are designed in such a way as to minimize the inaccuracy resulting from the use of an approximate linear model. This gives us very rich possibilities for exploring and interpreting the operation of the modelled system. An important advantage of the proposed approach is a set of new interpretability criteria of the knowledge represented by fuzzy rules. Taking them into account in the process of automatic model selection allows us to reach a compromise between the accuracy of modelling and the readability of fuzzy rules.
2
Content available New Methods for Designing and Reduction of Neuro-Fuzzy Systems
Cpałka K.
Journal of Applied Computer Science Methods
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2010
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Vol. 2 No. 2
113--126
EN
In the paper, we propose novel methods for designing and reduction of neuro-fuzzy systems without the deterioration of their accuracy. The reduction and merging algorithms gradually eliminate inputs, rules, antecedents, and the number of discretization points of integrals in the center of area defuzzification method. Our algorithms have been tested using well known classification benchmark.
3
Content available remote A flexible approach to fuzzy modelling
Rutkowski L., Cpałka K.
Automatyka / Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie
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2004
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T. 8, z. 3
247-252
EN
In this paper we present a new method to fuzzy modelling. The Mamdani type reasoning is combined with the logical approach. The results will be illustrated on typical benchmarks.
PL
W pracy zaprezentowano nową metodę rozmytego modelowania. Polega ona na odpowiednim połączeniu wnioskowania Mamdaniego i wnioskowania logicznego. Zaproponowane rozwiązanie zilustrowano wynikami symulacji.
4
Content available A neuro-fuzzy controller with a compromise fuzzy reasoning
Rutkowski L., Cpałka K.
Control and Cybernetics
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2002
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Vol. 31, no 2
297-308
EN
This paper presents a compromise approach to neuro-fuzzy controllers. It includes both Mamdani (constructive) and logical (destructive) fuzzy inference. New neuro-fuzzy controllers are derived and simulation results are presented.
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