%0 Computer Program %A Wullems, Bas %A Brauer, Claudia %A Weerts, Albrecht %A Baart, Fedor %D 2023 %T Code underlying the publication: Forecasting estuarine salt intrusion in the Rhine-Meuse delta using an LSTM model %U %R 10.4121/21946724.v3 %K Salt intrusion %K LSTM %K Machine learning %K Hydrology %K Water management %K Estuary %K Delta %K Forecasting %K chloride %K river %X

 

Machine learning model for predicting salt concentrations in the Rhine-Meuse delta.

The folder 'Data' contains processed data, identical to 'Features.csv' in the raw dataset.

The folder 'Models' contains an ensemble of LSTM models created with the script 'LSTMv1.py'.

The script 'preprocessing.py' was used to convert the raw data to the daily data in 'Features.csv'.

%I 4TU.ResearchData