A new predictive model based on the PSO-optimized support vector machine approach for predicting the milling tool wear from milling runs experimental data-Reference-Cited by-同舟云学术

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

Published:2015-12-23 Issue:1-4 Volume:86 Page:769-780
ISSN:0268-3768
Container-title:The International Journal of Advanced Manufacturing Technology
language:en
Short-container-title:Int J Adv Manuf Technol

Author:

García-Nieto P. J.,García-Gonzalo E.,Vilán Vilán J. A.,Segade Robleda A.

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering

Link

http://link.springer.com/content/pdf/10.1007/s00170-015-8148-1.pdf

Reference46 articles.

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5. Goebel K (1966) Management of uncertainty in sensor validation, sensor fusion, and diagnosis of mechanical systems using soft computing techniques. Ph.D. Dissertation, Department of Mechanical Engineering, University of California at Berkeley

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