Materials informatics-Reference-Cited by-同舟云学术

Materials informatics

Published:2018-01-17 Issue:6 Volume:30 Page:2307-2326
ISSN:0956-5515
Container-title:Journal of Intelligent Manufacturing
language:en
Short-container-title:J Intell Manuf

Author:

Ramakrishna Seeram^ORCID,Zhang Tong-Yi,Lu Wen-Cong,Qian Quan,Low Jonathan Sze Choong,Yune Jeremy Heiarii Ronald,Tan Daren Zong Loong,Bressan Stéphane,Sanvito Stefano,Kalidindi Surya R.

Funder

UK Lloyds Register Foundation

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering,Software

Link

http://link.springer.com/article/10.1007/s10845-018-1392-0/fulltext.html

Reference73 articles.

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3. Agrawal, A., Deshpande, P. D., Cecen, A., Gautham, B. P., Choudhary, A. N., & Kalidindi, S. R. (2014). Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters. Integrating Materials and Manufacturing Innovation, 3, 8. https://doi.org/10.1186/2193-9772-3-8 .

4. Astrup, T., Møller, J., & Fruergaard, T. (2009). Incineration and co-combustion of waste: Accounting of greenhouse gases and global warming contributions. Waste Management & Research, 27(8), 789–799. https://doi.org/10.1177/0734242X09343774 .

5. Balachandran, P. V., Xue, D., Theiler, J., Hogden, J., & Lookman, T. (2016). Adaptive strategies for materials design using uncertainties. Scientific Reports, 6 (1966).

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