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Z-number based fuzzy neural network for system identification.
- Source :
- Journal of Intelligent & Fuzzy Systems; 2023, Vol. 45 Issue 6, p11203-11216, 14p
- Publication Year :
- 2023
-
Abstract
- In this paper, a novel Z-number based Fuzzy Neural Network (Z-FNN) based on the integration of Z-valued fuzzy logic and neural networks is proposed. Z-valued fuzzy rule base is presented and its inference process is described using interpolative approximate reasoning. Accordingly, the structure of the Z-FNN is proposed using a distance measure and interpolative approximate reasoning scheme. Based on presented architecture the learning algorithm of Z-FNN is designed. The updating of the unknown parameters of the network is carried out using Genetic Algorithms (GA). The proposed Z-FNN system is utilized for dynamic plant identification. The effectiveness of Z-FNN has been tested by comparing its performance with the performances of other fuzzy systems available in the literature. The proposed approach has been proven to be a suitable alternative for the identification of nonlinear systems characterized by uncertain and imprecise information. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10641246
- Volume :
- 45
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 174544571
- Full Text :
- https://doi.org/10.3233/JIFS-232741