Using RBF nets in rubber industry process control

  • This paper describes the use of a radial basis function (RBF) neural network. It approximates the process parameters for the extrusion of a rubber profile used in tyre production. After introducing the problem, we describe the RBF net algorithm and the modeling of the industrial problem. The algorithm shows good results even using only a few training samples. It turns out that the „curse of dimensions“ plays an important role in the model. The paper concludes by a discussion of possible systematic error influences and improvements.

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Metadaten
Author:Ulf Pietruschka, Rüdiger W. BrauseGND
URN:urn:nbn:de:hebis:30-79071
Document Type:Article
Language:English
Date of Publication (online):2010/09/08
Year of first Publication:1996
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2010/09/08
Note:
Postprint, zuerst in: Proc. Int. Conf. on Art. Neural Networks ICANN-96, Lecture Notes in Computer Science LNCS 1112, Springer Verlag 1996, S. 605-610
Source:Proc. Int. Conf. on Art. Neural Networks ICANN-96; Lecture notes in computer science, LNCS ; 1112, Springer-Verl., 1996, pp. 605-610
HeBIS-PPN:227576918
Institutes:Informatik und Mathematik / Informatik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Sammlungen:Universitätspublikationen
Licence (German):License LogoDeutsches Urheberrecht

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