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Investigation and Prediction of ECMM characteristics of Hardened Die Steel with Nanoparticle Added Electrolytes Using Hybrid Deep Neural Network Cover

Investigation and Prediction of ECMM characteristics of Hardened Die Steel with Nanoparticle Added Electrolytes Using Hybrid Deep Neural Network

Green Sciences
Volume 24 (2022): Issue 4 (December 2022)
By: Vijayakumar Kanniyappan and  Sekar Tamilperuvalathan  
Open Access
|Dec 2022
DOI: https://doi.org/10.2478/pjct-2022-0024 | Journal eISSN: 3072-0389
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Language: English
Page range: 7 - 22
Published on: Dec 26, 2022
Published by: West Pomeranian University of Technology, Szczecin
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
ECMM,
Die hardened steel,
machining parameters,
RSM,
hybrid,
neural network,
prediction
Related subjects:
Industrial chemistry,
Biotechnology,
Chemical engineering,
Process engineering

© 2022 Vijayakumar Kanniyappan, Sekar Tamilperuvalathan, published by West Pomeranian University of Technology, Szczecin
This work is licensed under the Creative Commons Attribution 4.0 License.

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