%0 Generic
%A Koo, Ja-Ho
%A Abraham, Edo
%A Jonoski, Andreja
%A Solomatine, Dimitri
%D 2025
%T Codes underlying: Comparison of scenario reduction approaches for reservoir inflow scenarios generated by a Bayesian Neural Network
%U 
%R 10.4121/e343331b-496f-40ab-83eb-f546df6dffa6.v1
%K Wasserstein distance
%K energy distance
%K Euclidian distance
%K Manhattan distance
%K scenario reduction
%K BNN
%K scenario generation
%X <p>The data set and codes for a paper, Comparison of scenario reduction approaches for reservoir inflow scenarios generated by a Bayesian Neural Network.</p><p>Including reservoir inflow data for the Daecheong reservoir in South Korea, there are codes to build a BNN model with hyperparameter optimization using the TPE algorithm. In addition, codes for scenario reduction by four different measures, Wasserstein, energy, Euclidean, and Manhattan distances, are integrated.</p>
%I 4TU.ResearchData