Machine Learning Engineering Tool

The Machine Learning engineering tool uses a "Stokes-type" force formulation approximating the higher order force harmonics (2nd – 5th) by correlating them to powers of the linear force time series (Chen et al., 2018). 

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A Machine Learning Gaussian Process (GP) model (Tang et al., 2024) is used to expand the coefficients database established through our experimental and numerical tests, allowing predictions across a wider range of wave regimes. 

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The flowchart of the Stokes-Gaussian Process (Stokes-GP) Machine Learning engineering tool is given below.