An expert system for vibration-based surface roughness prediction using firefly algorithm and LSTM network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,General Engineering,Aerospace Engineering,Automotive Engineering,Industrial and Manufacturing Engineering,Applied Mathematics
Link
https://link.springer.com/content/pdf/10.1007/s40430-023-04341-4.pdf
Reference64 articles.
1. Liu D et al (2022) Kinematics and improved surface roughness model in milling. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-022-10729-8
2. Msaddek EB, Baili M, Bouaziz Z, Dessein G (2021) Surface roughness perfection by CAM interpolations. J Braz Soc Mech Sci Eng 43(8):1–13. https://doi.org/10.1007/s40430-021-03093-3
3. Hessainia Z, Belbah A, Athmane M, Mabrouki T, Rigal J (2013) On the prediction of surface roughness in the hard turning based on cutting parameters and tool vibrations. Measurement 46(5):1671–1681. https://doi.org/10.1016/j.measurement.2012.12.016
4. Bhardwaj B, Kumar R, Singh PK (2014) Prediction of surface roughness in turning of EN 353 using response surface methodology. Trans Indian Inst Metals 67:305–313. https://doi.org/10.1007/s12666-013-0346-7
5. Tomov M, Kuzinovski M, Cichosz P (2016) International journal of mechanical sciences development of mathematical models for surface roughness parameter prediction in turning depending on the process condition. Int J Mech Sci 113:120–132. https://doi.org/10.1016/j.ijmecsci.2016.04.015
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