IJPAM: Volume 80, No. 2 (2012)
MODEL INVERSION USING FUZZY NEURAL NETWORK
WITH BOOSTING OF THE SOLUTION
WITH BOOSTING OF THE SOLUTION
Paolo Mercorelli
, Mirko Nentwig
Leuphana University of Lueneburg
Institute of Product and Process Innovation
Volgershall 1, D-21339 Lueneburg, GERMANY
Audi AG
Department of Hardware-in-the-Loop Functional Testing
D-85045 Ingolstadt, GERMANY
, Mirko Nentwig
Leuphana University of Lueneburg
Institute of Product and Process Innovation
Volgershall 1, D-21339 Lueneburg, GERMANY
Audi AG
Department of Hardware-in-the-Loop Functional Testing
D-85045 Ingolstadt, GERMANY
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.
Received: September 18, 2012
AMS Subject Classification: 92B20, 03B52, 90B15
Key Words and Phrases: neural networks, fuzzy logic, networks model
Download paper from here.
Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2012
Volume: 80
Issue: 2
