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[5592] Artykuł:

Neuro-fuzzy systems for rule-based modelling of dynamic processes

Czasopismo: Proceedings of Fourth European Symposium on Intelligent Techniques (ESIT 2000), Aachen, Niemcy   Strony: 416-422
Opublikowano: 2000
 
  Autorzy / Redaktorzy / Twórcy
Imię i nazwisko Wydział Katedra Procent
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Marian Bolesław Gorzałczany orcid logoWEAiIKatedra Elektroniki i Systemów Inteligentnych *****50.00  
Adam Głuszek orcid logoWEAiIKatedra Elektroniki i Systemów Inteligentnych *****50.00  

Grupa MNiSW:  Recenzowany referat w materiałach konferencyjnych w języku angielskim
Punkty MNiSW: 0




Abstract:

The aim of this paper is to present and compare four different neuro-fuzzy approaches to the construction of fuzzy rule-based models for dynamic processes. These approaches have been applied to modelling of an industrial gas furnace system (Box-Jenkins benchmark). The following neuro-fuzzy systems have been considered: nfMod – the system proposed in this paper, the well-known ANFIS and NFIDENT systems, and an alternative neuro-fuzzy system reported in literature. The main criterion of comparison of all systems is their performance (the accuracy of modelling) versus interpretability (the transparency and the ability to explain generated decisions; it also includes an analysis and pruning of obtained fuzzy-rule bases).