High-performance prediction model combining minimum redundancy maximum relevance, circulant spectrum analysis, and machine learning methods for daily and peak streamflow-Reference-Cited by-同舟云学术

High-performance prediction model combining minimum redundancy maximum relevance, circulant spectrum analysis, and machine learning methods for daily and peak streamflow

Published:2023-09-19 Issue:1 Volume:155 Page:621-643
ISSN:0177-798X
Container-title:Theoretical and Applied Climatology
language:en
Short-container-title:Theor Appl Climatol

Author:

Latifoğlu Levent,Kaya Esra

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

https://link.springer.com/content/pdf/10.1007/s00704-023-04653-4.pdf

Reference67 articles.

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3. Ahmadi F, Tohidi M, Sadrianzade M (2023) Streamflow prediction using a hybrid methodology based on variational mode decomposition (VMD) and machine learning approaches. Appl Water Sci 13(6):135

4. Altman DG, Bland JM (1983) Measurement in medicine: the analysis of method comparison studies. J R Stat Soc Ser D Stat 32(3):307–317

5. Birikundavyi S, Labib R, Trung HT, Rousselle J (2002) Performance of neural networks in daily streamflow forecasting. J Hydrol Eng 7(5):392–398

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