Data of "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step."
<p>Data related to<br> ===========<br> title = "Recurrent Neural Networks (RNNs) with dimensionality reduction and break down in computational mechanics; application to multi-scale localization step.",<br> journal = "Computer Methods in Applied Mechanics and Engineering",<br> volume ="390",<br> year = "2022",<br> doi = "https://doi.org/<a href="http://dx.doi.org/10.1016/j.cma.2021.114476">10.1016/j.cma.2021.114476</a> ",<br> pages = "114476 ",<br> author = "Wu, Ling and Noels, Ludovic"</p> <p>We would be grateful if you could cite the paper in the case in which you are using the data</p> <p> </p> <p>The files replace version 1 whose zip was corrupted.</p> <p> </p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4