Study on Feature Selection and Identification Method of Tool Wear States Based on Svm

Online veröffentlicht: 10. Apr. 2013

Seitenbereich: 448 - 465

Eingereicht: 24. Jan. 2013

Akzeptiert: 12. März 2013

DOI: https://doi.org/10.21307/ijssis-2017-549

Schlüsselwörter

Tool condition monitoring, feature selection, multi-class support vector machine recursive feature elimination (SVM-RFE), least squares support vector machines (LS-SVM)

© 2013 Weilin Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.