RETRACTED: A Physics‐Aware Machine Learning‐Based Framework for Minimizing Prediction Uncertainty of Hydrological Models

Modeling hydrological processes for managing the available water resources effectively is often complex due to the existence of high nonlinearity, and the associated prediction uncertainty mainly arising from model inputs, parameters, and structure. Despite several attempts to quantify the model pre...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Water resources research Jg. 59; H. 6
Hauptverfasser:	Roy, Abhinanda, Kasiviswanathan, K. S., Patidar, Sandhya, Adeloye, Adebayo J., Soundharajan, Bankaru‐Swamy, Ojha, Chandra Shekhar P.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Washington John Wiley & Sons, Inc 01.06.2023 Wiley
Schlagworte:	HBV model particle filter technique random forest algorithm streamflow prediction interval uncertainty quantification
ISSN:	0043-1397, 1944-7973
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!