Combined data-driven model for the prediction of thermal properties of Ni-based amorphous alloys-Reference-Cited by-同舟云学术

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Combined data-driven model for the prediction of thermal properties of Ni-based amorphous alloys

Published:2022-01 Issue: Volume:16 Page:129-138
ISSN:2238-7854
Container-title:Journal of Materials Research and Technology
language:en
Short-container-title:Journal of Materials Research and Technology

Author:

Jeon Junhyub,Kim Gwanghun,Seo Namhyuk,Choi Hyunjoo,Kim Hwi-Jun,Lee Min-Ha,Lim Hyun-Kyu,Son Seung Bae,Lee Seok-Jae

Funder

Ministry of Trade, Industry and Energy

Korea Institute for Advancement of Technology

Publisher

Elsevier BV

Subject

Metals and Alloys,Surfaces, Coatings and Films,Biomaterials,Ceramics and Composites

Reference75 articles.

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3. A machine learning approach for engineering bulk metallic glass alloys;Ward;Acta Mater,2018

4. A two-stage predicting model for γ′ solvus temperature of L12-strengthened Co-base superalloys based on machine learning;Yu;Intermetallics,2019

5. Tensile properties prediction by multiple linear regression analysis for selective laser melted and post heat-treated Ti-6Al-4V with microstructural quantification;Kusano;Mater Sci Eng, A,2020

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