Flood forecasting and uncertainty analysis based on the combination of improved adaptive noise learning model and density estimation

Flood forecasting and uncertainty analysis based on the combination of improved adaptive noise learning model and density estimation

The strong randomness exhibited by runoff series means the accuracy of flood forecasting still needs to be improved. Mode mixing can be dealt with using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and the endpoint effect of CEEMDAN can be successfully dealt with usi...

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Bibliographic Details
Main Authors: Yang Liu, Shuaibing Du, Lihu Wang
Format: Article
Language:English
Published: IWA Publishing 2022-12-01
Series:Water Supply
Subjects:
broad learning
endpoint effect
flood forecasting
nonparametric kernel density estimation
orthogonal triangular matrix decomposition
Online Access:http://ws.iwaponline.com/content/22/12/8988

Internet

http://ws.iwaponline.com/content/22/12/8988

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