Citations (6)
Keep up to date with the latest research on this topic with citation updates for this article.
Read on this site (2)
Radha Pavanasam, Chandrasekaran G.N. Selvakumar. (2021) Deep learning-based supervised and unsupervised neural networks for analysing the characteristics of powder composite preforms. International Journal of Modelling and Simulation 41:6, pages 451-462.
Read now
Read now
G. Poshal & P. Ganesan. (2011) Constitutive analysis on formability of aluminium iron composite preforms using artificial neural network. Powder Metallurgy 54:1, pages 71-78.
Read now
Read now
Articles from other publishers (4)
P. Radha, G. Chandrasekaran & N. Selvakumar. (2015) Simplifying the powder metallurgy manufacturing process using soft computing tools. Applied Soft Computing 27, pages 191-204.
Crossref
Crossref
A Rajeshkannan, Devi S Rengamani & Alok Sharma. (2013) Some aspects on geometric and matrix work-hardening characteristics of sintered cold forged copper alloy preforms. Materials Research 17:1, pages 196-202.
Crossref
Crossref
G Poshal & P Ganesan. (2009) Neural network approach for the selection of processing parameters of aluminium—iron composite preforms during cold upsetting. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 224:3, pages 459-472.
Crossref
Crossref
G. Poshal & P. Ganesan. (2008) An analysis of formability of aluminium preforms using neural network. Journal of Materials Processing Technology 205:1-3, pages 272-282.
Crossref
Crossref