Have a personal or library account? Click to login
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: Weilin Li,  Pan Fu and  Weiqing Cao  
Open Access
|Apr 2013

Authors

Weilin Li

hiweilin@gmail.com

School of Mechanical Engineering Southwest Jiaotong University, China

Pan Fu

pfu@home.swjtu.edu.cn

School of Mechanical Engineering Southwest Jiaotong University, China

Weiqing Cao

School of Mechanical Engineering Southwest Jiaotong University, China
DOI: https://doi.org/10.21307/ijssis-2017-549 | Journal eISSN: 1178-5608
Journal RSS Feed
Language: English
Page range: 448 - 465
Submitted on: Jan 24, 2013
|
Accepted on: Mar 12, 2013
|
Published on: Apr 10, 2013
Published by: Professor Subhas Chandra Mukhopadhyay
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 Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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