Data-driven discovery of dimensionless numbers and governing laws from scarce measurements
Dimension reduction techniques allow to simplify complex process design and system optimization in various engineering problems. The authors propose here a machine learning approach to discover dominant dimensionless numbers and governing laws from scarce measurement data.
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-12-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-022-35084-w |