Model inversion using fuzzy neural network with boosting of the solution

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Model inversion using fuzzy neural network with boosting of the solution. / Mercorelli, P.; Nentwig, Mirko.
in: International Journal of Pure and Applied Mathematics, Jahrgang 80, Nr. 2, 2012, S. 261-270.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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@article{53001e5774da4658a04cce5868bd6140,
title = "Model inversion using fuzzy neural network with boosting of the solution",
abstract = "Neural networks are a very effective and popular tool for modeling. The inversion of a neural network makes possible the use of these networks in control problem schemes. This paper presents an inversion strategy based upon a feed-forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. AMS Subject Classification: 92B20, 03B52, 90B15",
keywords = "Engineering, Regelungstechnik, Antriebstechnik, Fuzzy logic, Networks model, Neural networks",
author = "P. Mercorelli and Mirko Nentwig",
note = "Copyright 2012 Elsevier B.V., All rights reserved.",
year = "2012",
language = "English",
volume = "80",
pages = "261--270",
journal = "International Journal of Pure and Applied Mathematics",
issn = "1311-8080",
publisher = "Academic Publications Ltd.",
number = "2",

}

RIS

TY - JOUR

T1 - Model inversion using fuzzy neural network with boosting of the solution

AU - Mercorelli, P.

AU - Nentwig, Mirko

N1 - Copyright 2012 Elsevier B.V., All rights reserved.

PY - 2012

Y1 - 2012

N2 - Neural networks are a very effective and popular tool for modeling. The inversion of a neural network makes possible the use of these networks in control problem schemes. This paper presents an inversion strategy based upon a feed-forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. AMS Subject Classification: 92B20, 03B52, 90B15

AB - Neural networks are a very effective and popular tool for modeling. The inversion of a neural network makes possible the use of these networks in control problem schemes. This paper presents an inversion strategy based upon a feed-forward trained local linear model tree. The local linear model tree is realized through a fuzzy neural network. AMS Subject Classification: 92B20, 03B52, 90B15

KW - Engineering

KW - Regelungstechnik

KW - Antriebstechnik

KW - Fuzzy logic

KW - Networks model

KW - Neural networks

UR - http://www.scopus.com/inward/record.url?scp=84867836477&partnerID=8YFLogxK

M3 - Journal articles

AN - SCOPUS:84867836477

VL - 80

SP - 261

EP - 270

JO - International Journal of Pure and Applied Mathematics

JF - International Journal of Pure and Applied Mathematics

SN - 1311-8080

IS - 2

ER -

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