Intuitionistic Neo-Fuzzy Network for modeling of nonlinear systems dynamics

Margarita Terziyska, Yancho Todorov

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)

Abstract

In this paper, an approach to design an Intuitionistic Neo-Fuzzy Network (INFN) is presented. The proposed architecture combines the advantages of the Intuitionistic Fuzzy Logic (IFL) to deal with uncertainties and the Neo-Fuzzy Neural Network approach to represent nonlinear systems with topologies including small number of parameters. As a learning approach for the consequent fuzzy rules parameters, the gradient optimization procedure is proposed. The investigate the potentials of the generated INF structure, the modeling of a three benchmark chaotic time series - Mackey-Glass, Lorenz and Rossler under uncertain conditions is investigated. The obtained results prove the flexibility of the approach and its further extension to Model Predictive Control is investigated too.

Original languageEnglish
Title of host publication2016 IEEE 8th International Conference on Intelligent Systems, IS 2016 - Proceedings
EditorsVassil Sgurev, Ronald Yager, Mincho Hadjiski, Vladimir Jotsov
PublisherInstitute of Electrical and Electronic Engineers IEEE
Pages616-621
ISBN (Electronic)978-1-5090-1354-8, 978-1-5090-1353-1
ISBN (Print)978-1-5090-1355-5
DOIs
Publication statusPublished - 7 Nov 2016
MoE publication typeA4 Article in a conference publication
Event8th IEEE International Conference on Intelligent Systems, IS 2016 - Sofia, Bulgaria
Duration: 4 Sep 20166 Sep 2016

Conference

Conference8th IEEE International Conference on Intelligent Systems, IS 2016
CountryBulgaria
CitySofia
Period4/09/166/09/16

Fingerprint

Nonlinear Dynamic System
Fuzzy neural networks
Model predictive control
Fuzzy rules
Fuzzy logic
Nonlinear systems
Time series
Topology
Glass
Chaotic Time Series
Intuitionistic Logic
Fuzzy Neural Network
Model Predictive Control
Fuzzy Rules
Modeling
Fuzzy Logic
Nonlinear Systems
Flexibility
Benchmark
Gradient

Keywords

  • chaotic time series
  • Intuitionistic Fuzzy Sets
  • Lorenz time series
  • Mackey-Glass time series
  • Model Predictive Control
  • Modelling
  • Neo-Fuzzy Network
  • Prediction
  • Rossler time series

Cite this

Terziyska, M., & Todorov, Y. (2016). Intuitionistic Neo-Fuzzy Network for modeling of nonlinear systems dynamics. In V. Sgurev, R. Yager, M. Hadjiski, & V. Jotsov (Eds.), 2016 IEEE 8th International Conference on Intelligent Systems, IS 2016 - Proceedings (pp. 616-621). [7737491] Institute of Electrical and Electronic Engineers IEEE. https://doi.org/10.1109/IS.2016.7737491
Terziyska, Margarita ; Todorov, Yancho. / Intuitionistic Neo-Fuzzy Network for modeling of nonlinear systems dynamics. 2016 IEEE 8th International Conference on Intelligent Systems, IS 2016 - Proceedings. editor / Vassil Sgurev ; Ronald Yager ; Mincho Hadjiski ; Vladimir Jotsov. Institute of Electrical and Electronic Engineers IEEE, 2016. pp. 616-621
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Terziyska, M & Todorov, Y 2016, Intuitionistic Neo-Fuzzy Network for modeling of nonlinear systems dynamics. in V Sgurev, R Yager, M Hadjiski & V Jotsov (eds), 2016 IEEE 8th International Conference on Intelligent Systems, IS 2016 - Proceedings., 7737491, Institute of Electrical and Electronic Engineers IEEE, pp. 616-621, 8th IEEE International Conference on Intelligent Systems, IS 2016, Sofia, Bulgaria, 4/09/16. https://doi.org/10.1109/IS.2016.7737491

Intuitionistic Neo-Fuzzy Network for modeling of nonlinear systems dynamics. / Terziyska, Margarita; Todorov, Yancho.

2016 IEEE 8th International Conference on Intelligent Systems, IS 2016 - Proceedings. ed. / Vassil Sgurev; Ronald Yager; Mincho Hadjiski; Vladimir Jotsov. Institute of Electrical and Electronic Engineers IEEE, 2016. p. 616-621 7737491.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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Terziyska M, Todorov Y. Intuitionistic Neo-Fuzzy Network for modeling of nonlinear systems dynamics. In Sgurev V, Yager R, Hadjiski M, Jotsov V, editors, 2016 IEEE 8th International Conference on Intelligent Systems, IS 2016 - Proceedings. Institute of Electrical and Electronic Engineers IEEE. 2016. p. 616-621. 7737491 https://doi.org/10.1109/IS.2016.7737491