cff-version: 1.2.0
abstract: "<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>"
authors:
  - family-names: Koo
    given-names: Ja-Ho
    orcid: "https://orcid.org/0000-0001-7100-8518"
  - family-names: Abraham
    given-names: Edo
  - family-names: Jonoski
    given-names: Andreja
    orcid: "https://orcid.org/0000-0002-0183-4168"
  - family-names: Solomatine
    given-names: Dimitri
title: "Codes underlying: Comparison of scenario reduction approaches for reservoir inflow scenarios generated by a Bayesian Neural Network"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/e343331b-496f-40ab-83eb-f546df6dffa6.v1
license: CC BY 4.0
date-released: 2025-03-25