Evaluation of Novel Soft Computing Methods for the Prediction of the Dental Milling Time-Error Parameter

Krömer, Pavel; Novosád, Tomáš; Vera González, Vicente; Hernando, Beatriz; García Hernández, Laura; Quintián Pardo, Héctor; Corchado Rodríguez, Emilio Santiago; Redondo Guevara, Raquel; Sedano Franco, Javier; García Barbero, Álvaro E.; Václav, Snášel

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Título

Evaluation of Novel Soft Computing Methods for the Prediction of the Dental Milling Time-Error Parameter

Autor(es)

Krömer, Pavel

Novosád, Tomáš

Vera González, Vicente

Hernando, Beatriz

García Hernández, Laura

Quintián Pardo, Héctor

Corchado Rodríguez, Emilio Santiago

Redondo Guevara, Raquel

Sedano Franco, Javier

García Barbero, Álvaro E.

Václav, Snášel

Palabras clave

Computer Science

Fecha de publicación

2013

Editor

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

https://hdl.handle.net/10366/135168

ISBN

978-3-642-32921-0 (Print) / 978-3-642-32922-7 (Online)

ISSN

2194-5357(Print)/ 2194-5365(Online)

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