Day-ahead inflow forecasting using causal empirical decomposition-Reference-Cited by-同舟云学术

Day-ahead inflow forecasting using causal empirical decomposition

Published:2022-10 Issue: Volume:613 Page:128265
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Yousefi Mojtaba^ORCID,Cheng Xiaomei,Gazzea Michele^ORCID,Wierling August Hubert,Rajasekharan Jayaprakash,Helseth Arild^ORCID,Farahmand Hossein,Arghandeh Reza

Funder

Høgskulen på Vestlandet

Norges Forskningsråd

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference46 articles.

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5. A multivariate streamflow forecasting model by integrating improved complete ensemble empirical mode decomposition with additive noise, sample entropy, gini index and sequence-to-sequence approaches;Apaydin;J. Hydrol.,2021

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