Printability for additive manufacturing with machine learning: Hybrid intelligent Gaussian process surrogate-based neural network model for Co-Cr alloy-Reference-Cited by-同舟云学术

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Printability for additive manufacturing with machine learning: Hybrid intelligent Gaussian process surrogate-based neural network model for Co-Cr alloy

Published:2022-11 Issue: Volume:135 Page:105428
ISSN:1751-6161
Container-title:Journal of the Mechanical Behavior of Biomedical Materials
language:en
Short-container-title:Journal of the Mechanical Behavior of Biomedical Materials

Author:

Mahmood Muhammad Arif^ORCID,Ur Rehman Asif,Karakaş Burak,Sever Ahmet,Ur Rehman Rashid^ORCID,Salamci Metin Uymaz^ORCID,Khraisheh Marwan

Funder

H2020 Marie Skłodowska-Curie Actions

European Commission Marie Sklodowska-Curie Actions

Horizon 2020 Framework Programme

European Commission

Publisher

Elsevier BV

Subject

Mechanics of Materials,Biomedical Engineering,Biomaterials

Reference49 articles.

1. Additive manufacturing of Co–Cr alloys for biomedical applications: a concise review;Acharya;J. Mater. Res.,2021

2. Anon Backpropagation - what Is the Meaning of the Error Rate in Neural Networks? - Cross Validated.

3. Anon Oerlikon Offers Metal Powders for 3D Printing | Oerlikon AM.

4. Anon Optional Accessories and Systems : SHIMADZU (Shimadzu Corporation).

5. Anon Standard Test Methods for Tension Testing of Metallic Materials.

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