Machine learning model for discrete, nonlinear datasets from machining operation: an industrial need to have high quality
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Mechanics of Materials,General Materials Science
Link
https://link.springer.com/content/pdf/10.1007/s41939-022-00118-9.pdf
Reference28 articles.
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3. Bose S, Nandi T (2021) RETRACTED: measurement of performance parameters and improvement in optimized solution of WEDM on a novel titanium hybrid composite. Measurement 171:108811. https://doi.org/10.1016/j.measurement.2020.108811
4. Çaydaş U, Ekici S (2012) Support vector machines models for surface roughness prediction in CNC turning of AISI 304 austenitic stainless steel. J Intell Manuf 23(3):639–650. https://doi.org/10.1007/s10845-010-0415-2
5. Chabbi A, Yallese MA, Nouioua M, Meddour I, Mabrouki T, Girardin F (2017) Modeling and optimization of turning process parameters during the cutting of polymer (POM C) based on RSM, ANN, and DF methods. Int J Adv Manuf Technol 91(5–8):2267–2290. https://doi.org/10.1007/s00170-016-9858-8
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