Model inversion using fuzzy neural network with boosting of the solution

P. Mercorelli; Mirko Nentwig

Model inversion using fuzzy neural network with boosting of the solution

P. Mercorelli
, Mirko Nentwig

Professur für Regelungs- und Antriebstechnik

AUDI AG

Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › Begutachtung

1 Zitat (Scopus)

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

Originalsprache	Englisch
Zeitschrift	International Journal of Pure and Applied Mathematics
Jahrgang	80
Ausgabenummer	2
Seiten (von - bis)	261-270
Seitenumfang	10
ISSN	1311-8080
Publikationsstatus	Erschienen - 2012

Fachgebiete und Schlagwörter

Ingenieurwissenschaften
Regelungstechnik
Antriebstechnik

ASJC Scopus Sachgebiete

Angewandte Mathematik
Mathematik (insg.)

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KW - Regelungstechnik

KW - Antriebstechnik

KW - Fuzzy logic

KW - Networks model

KW - Neural networks

UR - https://www.scopus.com/pages/publications/84867836477

M3 - Journal articles

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EP - 270

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Model inversion using fuzzy neural network with boosting of the solution

Abstract

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