Application of Artificial Neural Network to Predicting Hardenability of Gear Steel

Autor:	Ping Zhou, Xian-bin Du, Chunlin Qiu, Xiuhua Gao, Kemin Qi, Tian-yong Deng
Rok vydání:	2006
Předmět:	Engineering Software Artificial neural network Mechanics of Materials business.industry Simple (abstract algebra) Metallic materials Metallurgy Materials Chemistry Metals and Alloys business Process engineering Hardenability
Zdroj:	Journal of Iron and Steel Research International. 13:71-73
ISSN:	2210-3988 1006-706X
DOI:	10.1016/s1006-706x(06)60114-3
Popis:	The prediction of the hardenability and chemical composition of gear steel was studied using artificial neural networks. A software was used to quantitatively forecast the hardenability by its chemical composition or the chemical composition by its hardenability. The prediction result is more precise than that obtained from the traditional method based on the simple mathematical regression model.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::40e38eb15a81f5d35de0a2cbf2632018 https://doi.org/10.1016/s1006-706x(06)60114-3 Zobrazit plný text záznamu Full Text from ScienceDirect Full text from SpringerLink