Comparison of scenario reduction approaches for reservoir inflow timeseries generated by a Bayesian Neural Network.
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| Title: | Comparison of scenario reduction approaches for reservoir inflow timeseries generated by a Bayesian Neural Network. |
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| Authors: | Koo JH; Department of Water Management, Delft University of Technology, CN, Delft, The Netherlands.; Department of Hydroinformatics and Socio-Technical Innovation, IHE Delft, AX, Delft, The Netherlands.; Korea Water Resource Public Corporation, Daejeon, Republic of Korea., Abraham E; Department of Water Management, Delft University of Technology, CN, Delft, The Netherlands., Jonoski A; Department of Hydroinformatics and Socio-Technical Innovation, IHE Delft, AX, Delft, The Netherlands., Solomatine DP; Department of Water Management, Delft University of Technology, CN, Delft, The Netherlands.; Department of Hydroinformatics and Socio-Technical Innovation, IHE Delft, AX, Delft, The Netherlands.; Department of river basins hydrology, Water Problems Institute of RAS, Gubkina 3, Moscow, Russia. |
| Source: | PloS one [PLoS One] 2026 May 27; Vol. 21 (5), pp. e0350095. Date of Electronic Publication: 2026 May 27 (Print Publication: 2026). |
| Publication Type: | Journal Article; Comparative Study |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0350095 |
