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Titolo
Evaluation of Novel Soft Computing Methods for the Prediction of the Dental Milling Time-Error Parameter
Autor(es)
Soggetto
Computer Science
Fecha de publicación
2013
Editore
Springer Science + Business Media
Citación
Soft Computing Models in Industrial and Environmental Applications Advances in Intelligent Systems and Computing. Advances in Intelligent Systems and Computing. Volumen 188, pp. 163-172.
Resumen
This multidisciplinary study presents the application of two well known soft computing methods – flexible neural trees, and evolutionary fuzzy rules – for the prediction of the error parameter between real dental milling time and forecast given by the dental milling machine. In this study a real data set obtained by a dynamic machining center with five axes simultaneously is analyzed to empirically test the novel system in order to optimize the time error.
URI
ISBN
978-3-642-32921-0 (Print) / 978-3-642-32922-7 (Online)
ISSN
2194-5357(Print)/ 2194-5365(Online)
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- BISITE. Congresos [232]
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