Hydrological probabilistic forecasting based on deep learning and Bayesian optimization algorithm

Hydrological probabilistic forecasting based on deep learning and Bayesian optimization algorithm

Obtaining accurate runoff prediction results and quantifying the uncertainty of the forecasting are critical to the planning and management of water resources. However, the strong randomness of runoff makes it difficult to predict. In this study, a hybrid model based on XGBoost (XGB) and Gaussian pr...

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Bibliographic Details
Main Authors: Haijun Bai, Guanjun Li, Changming Liu, Bin Li, Zhendong Zhang, Hui Qin
Format: Article
Language:English
Published: IWA Publishing 2021-08-01
Series:Hydrology Research
Subjects:
bayesian optimization algorithm
gaussian process regression
probabilistic forecasting
runoff
xgboost
Online Access:http://hr.iwaponline.com/content/52/4/927

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