Prediction of dental milling time-error by flexible neural trees and fuzzy rules
2012
This multidisciplinary study presents the application of two soft computing methods utilizing the artificial evolution of symbolic structures --- evolutionary fuzzy rules and flexible neural trees --- for the prediction of dental milling time-error, i.e. the error 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.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
16
References
0
Citations
NaN
KQI