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

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

International Journal on Smart Sensing and Intelligent Systems
Volume 6 (2013): Issue 2 (January 2013)
By: ,   and    
Open Access
|Apr 2013
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DOI: https://doi.org/10.21307/ijssis-2017-549 | Journal eISSN: 1178-5608
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Language: English
Page range: 448 - 465
Submitted on: Jan 24, 2013
Accepted on: Mar 12, 2013
Published on: Apr 10, 2013
Published by: Macquarie University, Australia
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Tool condition monitoring,
feature selection,
multi-class support vector machine recursive feature elimination (SVM-RFE),
least squares support vector machines (LS-SVM)
Related subjects:
Engineering,
Introductions and overviews,
Engineering, other

© 2013 Weilin Li, Pan Fu, Weiqing Cao, published by Macquarie University, Australia
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 6 (2013): Issue 2 (January 2013)
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