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Enhancing streamflow drought prediction: integrating wavelet decomposition with deep learning and quantile regression neural network models
SMHI, Research Department, Hydrology.ORCID iD: 0000-0001-8427-5965
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2025 (English)In: EARTH SCIENCE INFORMATICS, ISSN 1865-0473, Vol. 18, no 2, article id 232Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2025. Vol. 18, no 2, article id 232
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Oceanography, Hydrology and Water Resources
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Hydrology
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URN: urn:nbn:se:smhi:diva-6710DOI: 10.1007/s12145-025-01736-wISI: 001413337300007OAI: oai:DiVA.org:smhi-6710DiVA, id: diva2:1936563
Available from: 2025-02-11 Created: 2025-02-11 Last updated: 2025-06-12Bibliographically approved

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Enhancing streamflow drought prediction: integrating wavelet decomposition with deep learning and quantile regression neural network models(3072 kB)41 downloads
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File name FULLTEXT01.pdfFile size 3072 kBChecksum SHA-512
aae0822801ac83286b71337ab2a75238336aaf05d2773e17b6ca06d964831c81ed5e8dcae8dff4fe23b4a3b3c8984477093ce98c979d7a3d09c1b9c39fffc712
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Mohammadi, Babak

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