A comparative study of machine learning algorithms in the prediction of bead geometry in wire-arc additive manufacturing
Author:
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Modeling and Simulation
Link
https://link.springer.com/content/pdf/10.1007/s12008-023-01326-4.pdf
Reference40 articles.
1. Kotsiopoulos, T., Sarigiannidis, P., Ioannidis, D., Tzovaras, D.: Machine learning and deep learning in smart manufacturing: the smart grid paradigm. Comput. Sci. Rev. 40, 100341 (2021). https://doi.org/10.1016/j.cosrev.2020.100341
2. Oladipupo, T.: Types of machine learning algorithms. New Adv. Mach. Learn. (2010). https://doi.org/10.5772/9385
3. Johnson, N.S., et al.: Invited review: machine learning for materials developments in metals additive manufacturing. Addit. Manuf. (2020). https://doi.org/10.1016/j.addma.2020.101641
4. Guo, S., et al.: Machine learning for metal additive manufacturing: towards a physics-informed data-driven paradigm. J. Manuf. Syst. 62, 145–163 (2022). https://doi.org/10.1016/j.jmsy.2021.11.003
5. Nasiri, S., Khosravani, M.R.: Machine learning in predicting mechanical behavior of additively manufactured parts. J. Mater. Res. Technol. 14, 1137–1153 (2021). https://doi.org/10.1016/j.jmrt.2021.07.004
Cited by 5 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. State-of-art review on the process-structure-properties-performance linkage in wire arc additive manufacturing;Virtual and Physical Prototyping;2024-09-05
2. Improving the Interpretability of Data-Driven Models for Additive Manufacturing Processes Using Clusterwise Regression;Mathematics;2024-08-19
3. Application of artificial intelligence in additive manufacturing;JMST Advances;2023-12
4. Mechanical Properties of Wire Arc Additive Manufactured 5356 Aluminum Alloy Wall Using Robotic-Controlled GMAW;Metallography, Microstructure, and Analysis;2023-11-07
5. Deep learning-based framework for the observation of real-time melt pool and detection of anomaly in wire-arc additive manufacturing;Materials and Manufacturing Processes;2023-09-05
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3