Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms

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Detalles Bibliográficos
Publicado en:	PLoS One vol. 20, no. 6 (Jun 2025), p. e0324049
Autor principal:	Jatti, Vijaykumar S
Otros Autores:	Saiyathibrahim, A, Yadav, Arvind, Murali, Krishnan R, Jayaprakash, B, Kaushal, Sumit, Jatti, Vinaykumar S, Jatti, Ashwini V, Jatti, Savita V, Kumar, Abhinav, Gouadria, Soumaya, Bonyah, Ebenezer
Publicado:	Public Library of Science
Materias:	Solidification Tensile properties Regression analysis Heat treatment Aviation Heat Machine learning Additive manufacturing Learning algorithms Decision trees Regression Lasers Root-mean-square errors Neural networks Computer aided design > CAD 3-D printers Algorithms Gaussian process Stainless steel Methods Alloys Aluminum base alloys Product development Economic
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