Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning-Reference-Cited by-同舟云学术

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Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

Published:2024-04 Issue:4 Volume:12 Page:1518-1528
ISSN:2213-9567
Container-title:Journal of Magnesium and Alloys
language:en
Short-container-title:Journal of Magnesium and Alloys

Author:

Maqbool Annayath^ORCID,Khalad Abdul,Khan Noor Zaman

Publisher

Elsevier BV

Reference43 articles.

1. Towards Mg Based Light Materials of Future: Properties, Applications, Problems, and Their Mitigation

2. Influence of bimodal grain size distribution on the corrosion behavior of friction stir processed biodegradable AZ31 magnesium alloy

3. Research and development status of laser cladding on magnesium alloys: A review

4. Insight of magnesium alloys and composites for orthopedic implant applications – a review

5. Magnesium based surface metal matrix composites by friction stir processing

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Construction of Prediction Models of Mass Ablation Rate for Silicone Rubber-Based Flexible Ablative Composites Based on a Small Dataset;Applied Sciences;2024-09-07

2. A brief review of machine learning-assisted Mg alloy design, processing, and property predictions;Journal of Materials Research and Technology;2024-05

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