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

The main aim of this research work is to build a new practical hybrid regression model to predict the milling tool wear in a regular cut as well as entry cut and exit cut of a milling tool. The model was based on particle swarm optimization (PSO) in combination with support vector machines (SVMs). T...

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Veröffentlicht in:	International journal of advanced manufacturing technology 2016-09, Vol.86 (1-4), p.769-780
Hauptverfasser:	García-Nieto, P. J., García-Gonzalo, E., Vilán Vilán, J. A., Segade Robleda, A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Bearing CAE) and Design Computer-Aided Engineering (CAD Engineering Industrial and Production Engineering Mechanical Engineering Media Management Milling (machining) Milling machines Original Article Particle swarm optimization Regression models Support vector machines Tool wear
Online-Zugang:	Volltext
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