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[30832] Artykuł:

A neuro-fuzzy approach to system modelling. Part II. Applications

Czasopismo: Archives of Control Sciences   Tom: 7(XLIII), Zeszyt: 3-4, Strony: 267-284
ISSN:  0004-072X
Opublikowano: 1998
 
  Autorzy / Redaktorzy / Twórcy
Imię i nazwisko Wydział Katedra Procent
udziału		 Liczba
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Marian Bolesław Gorzałczany orcid logoWEAiIKatedra Elektroniki i Systemów Inteligentnych *****100.00  

Grupa MNiSW:  Publikacja w recenzowanym czasopiśmie wymienionym w wykazie ministra MNiSzW (część B)
Punkty MNiSW: 0

Keywords:

neuro-fuzzy systems  fuzzy controllers  identification methods  artificial neural networks  fuzzy sets  fuzzy models  fuzzy neural networks 


Abstract:

The description of behaviour of complex and ill-defined systems and processes is usually based on a combination of two types of knowledge and data: a qualitative, fuzzy knowledge which contains elements of uncertainty and vagueness and often is expressed in the form of linguistic rules usually provided by a domain expert, and a quantitative, nonfuzzy information which appears in the form of measurements and other numerical data. Part I (ACS No. 1/2 1998) of this paper presents a methodology for modelling of complex systems which can effectively represent, process and generalize both mentioned-above types of system's knowledge. The proposed methodology combines artificial neural networks with some elements of the theory of fuzzy sets and fuzzy logic, yielding a structure that can be called a fuzzy neural network or a neuro-fuzzy system. Two examples of the application of our approach in the area of system modelling are presented in Part II of the paper.


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