BeuzenEtAl_2019_NHESS_GP_runup_model
Wave prediction model
Reproducible research on predicting wave runup and coastal dune erosion using Gaussian processes
Repository for the Beuzen et al (2019) paper "Ensemble models from machine learning: an example of wave runup and coastal dune erosion."
5 stars
3 watching
1 forks
Language: Jupyter Notebook
last commit: over 5 years ago
Linked from 1 awesome list
Related projects:
| Repository | Description | Stars |
|---|---|---|
| tomasbeuzen/ph12_dune_erosion_model | An ensemble version of the LEH 2004 dune erosion model implemented in Matlab and Python for simulating environmental processes. | 0 |
 chrisleaman/py-wave-runup | Empirical wave runup models implemented in Python for coastal engineers and scientists. | 39 |
 damitkwr/esrnn-gpu | A PyTorch implementation of an optimized deep learning model for time series forecasting on GPUs. | 319 |
 anellenson/decisiontree_waveforecasts | An application of machine learning to analyze wave model output and identify error patterns | 2 |
 ecmwfcode4earth/ml_drought | Develops machine learning models to predict and understand drought using climate science data | 93 |
 grootzz/ga-bp | An optimization framework using genetic algorithms to train and improve the performance of Backpropagation Neural Networks for traffic flow prediction | 157 |
 storm-fsv-cvut/smoderp2d | A distributed event-based model for simulating surface and subsurface runoff and erosion processes. | 9 |
 stormsurgelive/asgs | Automates coastal ocean modelling for real-time decision support using Fortran. | 39 |
 wpringle/glocoffs | Real-time coastal flooding forecasting system using ADCIRC-based storm tide modeling | 16 |
 mdh266/nycbuildingenergyuse | Developing regression models to predict greenhouse gas emissions from building energy usage using Google Cloud and machine learning techniques | 19 |
 colasgael/machine-learning-for-solar-energy-prediction | Develops a predictive model to forecast the power production of solar panels based on weather data | 240 |
 boldingbruggeman/getm-rewrite | A Python and Fortran-based implementation of the General Estuarine Transport Model | 6 |
 tetratech/baytrends | A package that enables evaluation of long-term trends in water quality data using Generalized Additive Modeling (GAM) approach | 12 |
 sheffieldml/multigp | Software for modeling and prediction with multiple output Gaussian processes | 48 |
 umn-hydro/gsflow-grass | Generates inputs and runs the coupled groundwater-surface water model GSFLOW using GRASS GIS. | 29 |