A hybrid, genetic programming and physically-based predictor of dune geometry

Created by W.Langdon from gp-bibliography.bib Revision:1.8414

@Article{Dore:2025:geomorph,

• author = "Arnaud Dore and Giovanni Coco",
• title = "A hybrid, genetic programming and physically-based predictor of dune geometry",
• journal = "Geomorphology",
• year = "2025",
• volume = "468",
• pages = "109495",
• keywords = "genetic algorithms, genetic programming, Dunes, Machine learning, Global sensitivity analysis",
• ISSN = "0169-555X",
• URL = "https://www.sciencedirect.com/science/article/pii/S0169555X24004471",
• DOI = "doi:10.1016/j.geomorph.2024.109495",
• abstract = "Subaqueous sand dunes are found in many natural environments and pose significant operational challenges. However, classic dune predictors found in the literature fail at predicting equilibrium dune dimensions. In this study, we first investigated the potential of using genetic programming to derive predictive equations of dune wavelength and height. The predictors outperformed existing relationships, yet the equations remain complex due to the intricate physics governing dune evolution. We carried out a global sensitivity analysis to evaluate the most influential parameters of the GP predictors. Finally, we proposed a set of robust predictors, for equilibrium dune heights and wavelengths, relying on basic environmental parameters",

}

Genetic Programming entries for Arnaud Dore Giovanni Coco

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