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Characterization and Generation of 3D Realistic Geological Particles with Metaball Descriptor based on X-Ray Computed Tomography
This algorithm can capture the main contour of parental particles with a series of non-overlapping spheres and refine surface-texture details through gradient search.
A Data-driven feature selection and machine-learning model benchmark for the prediction of longitudinal dispersion coefficient
Then, a global optimal feature set (the channel width, the flow velocity, the channel slope and the cross sectional area) was proposed through numerical comparison of the distilled local optimums in performance with representative ML models.
A data-based comparative review and AI-driven symbolic model for longitudinal dispersion coefficient in natural streams
Whereas implicit ML-driven methods are black-boxes in nature, explicit ML-driven methods have more potential in prediction of LDC.
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