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On-line Design of Takagi-Sugeno Models.

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On-line Design of Takagi-Sugeno Models. / Angelov, Plamen; Filev, Dimitar.
Fuzzy Sets and Systems – IFSA 2003. ed. / T. Biglic; B. de Baets; O. Kaynak. Vol. 2715/2 2715/2. ed. Berlin/Heidelberg: Springer, 2003. p. 576-584 (Lecture Notes in Computer Science).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

Harvard

Angelov, P & Filev, D 2003, On-line Design of Takagi-Sugeno Models. in T Biglic, B de Baets & O Kaynak (eds), Fuzzy Sets and Systems – IFSA 2003. 2715/2 edn, vol. 2715/2, Lecture Notes in Computer Science, Springer, Berlin/Heidelberg, pp. 576-584. <http://www.springerlink.com/content/6rnbq8cv5rg6bkk5/>

APA

Angelov, P., & Filev, D. (2003). On-line Design of Takagi-Sugeno Models. In T. Biglic, B. de Baets, & O. Kaynak (Eds.), Fuzzy Sets and Systems – IFSA 2003 (2715/2 ed., Vol. 2715/2, pp. 576-584). (Lecture Notes in Computer Science). Springer. http://www.springerlink.com/content/6rnbq8cv5rg6bkk5/

Vancouver

Angelov P, Filev D. On-line Design of Takagi-Sugeno Models. In Biglic T, de Baets B, Kaynak O, editors, Fuzzy Sets and Systems – IFSA 2003. 2715/2 ed. Vol. 2715/2. Berlin/Heidelberg: Springer. 2003. p. 576-584. (Lecture Notes in Computer Science).

Author

Angelov, Plamen ; Filev, Dimitar. / On-line Design of Takagi-Sugeno Models. Fuzzy Sets and Systems – IFSA 2003. editor / T. Biglic ; B. de Baets ; O. Kaynak. Vol. 2715/2 2715/2. ed. Berlin/Heidelberg : Springer, 2003. pp. 576-584 (Lecture Notes in Computer Science).

Bibtex

@inbook{4bc77534cef34b46ab0022fce8c73d9c,
title = "On-line Design of Takagi-Sugeno Models.",
abstract = "An approach to the on-line design of Takagi-Sugeno type fuzzy models is presented in the paper. It combines supervised and unsupervised learning and recursively updates both the model structure and parameters. The rule-base gradually evolves increasing its summarization power. This approach leads to the concept of the evolving Takagi-Sugeno model. Due to the gradual update of the rule structure and parameters, it adapts to the changing data pattern. The requirement for update of the rule-base is based on the spatial proximity and is a quite strong one. As a result, the model evolves to a compact set of fuzzy rules, which adds to the interpretability, a property especially useful in fault detection. Other possible areas of application are adaptive non-linear control, time series forecasting, knowledge extraction, robotics, behavior modeling. The results of application to the on-line modeling the fermentation of Kluyveromyces lactis illustrate the efficiency of the approach. (c) Springer",
keywords = "DCS-publications-id, incoll-65, DCS-publications-credits, dsp-fa, DCS-publications-personnel-id, 82",
author = "Plamen Angelov and Dimitar Filev",
year = "2003",
language = "English",
isbn = "978-3-540-40383-8",
volume = "2715/2",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "576--584",
editor = "T. Biglic and {de Baets}, B. and O. Kaynak",
booktitle = "Fuzzy Sets and Systems – IFSA 2003",
edition = "2715/2",

}

RIS

TY - CHAP

T1 - On-line Design of Takagi-Sugeno Models.

AU - Angelov, Plamen

AU - Filev, Dimitar

PY - 2003

Y1 - 2003

N2 - An approach to the on-line design of Takagi-Sugeno type fuzzy models is presented in the paper. It combines supervised and unsupervised learning and recursively updates both the model structure and parameters. The rule-base gradually evolves increasing its summarization power. This approach leads to the concept of the evolving Takagi-Sugeno model. Due to the gradual update of the rule structure and parameters, it adapts to the changing data pattern. The requirement for update of the rule-base is based on the spatial proximity and is a quite strong one. As a result, the model evolves to a compact set of fuzzy rules, which adds to the interpretability, a property especially useful in fault detection. Other possible areas of application are adaptive non-linear control, time series forecasting, knowledge extraction, robotics, behavior modeling. The results of application to the on-line modeling the fermentation of Kluyveromyces lactis illustrate the efficiency of the approach. (c) Springer

AB - An approach to the on-line design of Takagi-Sugeno type fuzzy models is presented in the paper. It combines supervised and unsupervised learning and recursively updates both the model structure and parameters. The rule-base gradually evolves increasing its summarization power. This approach leads to the concept of the evolving Takagi-Sugeno model. Due to the gradual update of the rule structure and parameters, it adapts to the changing data pattern. The requirement for update of the rule-base is based on the spatial proximity and is a quite strong one. As a result, the model evolves to a compact set of fuzzy rules, which adds to the interpretability, a property especially useful in fault detection. Other possible areas of application are adaptive non-linear control, time series forecasting, knowledge extraction, robotics, behavior modeling. The results of application to the on-line modeling the fermentation of Kluyveromyces lactis illustrate the efficiency of the approach. (c) Springer

KW - DCS-publications-id

KW - incoll-65

KW - DCS-publications-credits

KW - dsp-fa

KW - DCS-publications-personnel-id

KW - 82

M3 - Chapter

SN - 978-3-540-40383-8

VL - 2715/2

T3 - Lecture Notes in Computer Science

SP - 576

EP - 584

BT - Fuzzy Sets and Systems – IFSA 2003

A2 - Biglic, T.

A2 - de Baets, B.

A2 - Kaynak, O.

PB - Springer

CY - Berlin/Heidelberg

ER -