Evaluation of neural network parameters in the prediction of AISI 1050 steel machining performance-Reference-Cited by-同舟云学术

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Evaluation of neural network parameters in the prediction of AISI 1050 steel machining performance

Published:2022-09-05 Issue: Volume: Page:1-12
ISSN:2374-068X
Container-title:Advances in Materials and Processing Technologies
language:en
Short-container-title:Advances in Materials and Processing Technologies

Author:

Sada S. O.¹,Eyenubo O. J.²,Atikpo E.³,Enyi C. L.¹

Affiliation:

1. Department of Mechanical Engineering, Faculty of Engineering, Oleh Campus, Delta State University, Oleh, Nigeria

2. Department of Electrical Engineering, Faculty of Engineering, Oleh Campus, Delta State University, Oleh, Nigeria

3. Department of Civil & Environmental Engineering, Faculty of Engineering, Oleh Campus, Delta State University, Oleh, Nigeria

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Mechanics of Materials,General Materials Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/2374068X.2022.2119715

Reference46 articles.

1. Response Surface Methodology and Genetic Algorithm used to Optimize the Cutting condition for Surface Roughness Parameters in CNC Turning

2. Predicting surface roughness in machining: a review

3. Processing of T6 heat-treated Al-12Si-0.6Mg alloy

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Evaluation of the optimal cutting performance of high-speed steel and tungsten carbide cutting tools in the machining of AISI 304 steel;The International Journal of Advanced Manufacturing Technology;2024-01-05

2. Evaluation of the optimal cutting performance of high speed steel and tungsten carbide cutting tools in the machining of aisi 304 steel.;2023-11-07

3. Prediction of Weld Geometry in Laser Welding by Numerical Simulation & Artificial Neural Networking;Advances in Materials and Processing Technologies;2023-05-11

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