• Corpus ID: 246706167

Dimensionally Consistent Learning with Buckingham Pi

@article{Bakarji2022DimensionallyCL,
  title={Dimensionally Consistent Learning with Buckingham Pi},
  author={Joseph Bakarji and Jared L. Callaham and Steven L. Brunton and J. Nathan Kutz},
  journal={ArXiv},
  year={2022},
  volume={abs/2202.04643}
}
In the absence of governing equations, dimensional analysis is a robust technique for extracting insights and finding symmetries in physical systems. Given measurement variables and parameters, the Buckingham Pi theorem provides a procedure for finding a set of dimensionless groups that spans the solution space, although this set is not unique. We propose an automated approach using the symmetric and self-similar structure of available measurement data to discover the dimensionless groups that… 

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