A new predictive model based on the PSO-optimized support vector machine approach for predicting the milling tool wear from milling runs experimental data

2015 ◽  
Vol 86 (1-4) ◽  
pp. 769-780 ◽  
Author(s):  
P. J. García-Nieto ◽  
E. García-Gonzalo ◽  
J. A. Vilán Vilán ◽  
A. Segade Robleda
Keyword(s):  
Experimental Data ◽  
Support Vector Machine ◽  
Tool Wear ◽  
Predictive Model ◽  
Support Vector ◽  
Model Based ◽  
Milling Tool

scholarly journals A Novel Hybrid Model Based on TVIW-PSO-GSA Algorithm and Support Vector Machine for Classification Problems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 27789-27801 ◽  
Author(s):  
Hongxin Xue ◽  
Yanping Bai ◽  
Hongping Hu ◽  
Ting Xu ◽  
Haijian Liang
Keyword(s):  
Support Vector Machine ◽  
Hybrid Model ◽  
Support Vector ◽  
Classification Problems ◽  
Model Based
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