A study on the performance of various predictive models based on artificial neural network for backward metal flow forming process-Reference-Cited by-同舟云学术

A study on the performance of various predictive models based on artificial neural network for backward metal flow forming process

Published:2022-10-30 Issue: Volume: Page:
ISSN:1955-2513
Container-title:International Journal on Interactive Design and Manufacturing (IJIDeM)
language:en
Short-container-title:Int J Interact Des Manuf

Author:

Banerjee Prabas^ORCID,Laha Rupam,Dikshit Mithilesh K.,Hui Nirmal Baran,Rana Subrata,Pathak Vimal Kumar,Saxena Kuldeep K.,Prakash Chander,Buddhi Dharam

Publisher

Springer Science and Business Media LLC

Subject

Industrial and Manufacturing Engineering,Modeling and Simulation

Link

https://link.springer.com/content/pdf/10.1007/s12008-022-01079-6.pdf

Reference41 articles.

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3. Awasthi, A., Saxena, K.K., Arun, V.: Sustainable and smart metal forming manufacturing process. Mater. Today Proc. 44, 2069–2079 (2021)

4. Banerjee, P., Hui, N.B.: A simplified model for the estimation of forces in flow forming and its comparison with ideal deformation and FEM models. J. Inst. Eng. India Ser. C 102(1), 13–26 (2021)

5. Bod´en, M.: A Guide to Recurrent Neural Networks and Backpropagation. Dallas Project, London (2002)

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