Published June 6, 2023 | Version 1
Dataset Open

Improving Shoreline Forecasting Models with Multi-Objective Genetic Programming

Authors/Creators

  • 1. LEGOS/ISAE-SUPAERO
  • 2. IRD
  • 3. CNES
  • 4. ISAE-SUPAERO

Description

This repository provides the processed data and the evolved models presented in the article. The following data sources were used to gather the raw data for each site:

 

The following files are provided here:

  • Sites_X_sla_ewave_rivdis.mat: contains the processed data compiled from the different raw sources.
  • models.zip: includes the raw outputs from the experiments described in the article, including the evolved model genomes and the log file of each run.

Files

models.zip

Files (417.5 MB)

Name Size
md5:c970b8ceea1dea8042df35468d0bc30d
417.5 MB Preview Download
md5:c62764532a45861124fd7ad401f52a82
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Additional details

References

  • Abessolo, G. O., Almar, R., Jouanno, J., Bonou, F., Castelle, B., & Larson, M. (2020). Beach adaptation to intraseasonal sea level changes. Environmental Research Communications, 2(5), 051003.
  • Turner, I., Harley, M., Short, A. et al. A multi-decade dataset of monthly beach profile surveys and inshore wave forcing at Narrabeen, Australia. Sci Data 3, 160024 (2016). https://doi.org/10.1038/sdata.2016.24
  • Ludka, B.C., Guza, R.T., O'Reilly, W.C. et al. Sixteen years of bathymetry and waves at San Diego beaches. Sci Data 6, 161 (2019). https://doi.org/10.1038/s41597-019-0167-6
  • Castelle, B., Bujan, S., Marieu, V. et al. 16 years of topographic surveys of rip-channelled high-energy meso-macrotidal sandy beach. Sci Data 7, 410 (2020). https://doi.org/10.1038/s41597-020-00750-5