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Data-driven decadal climate forecasting using Wasserstein time-series generative adversarial networks.

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Title: Data-driven decadal climate forecasting using Wasserstein time-series generative adversarial networks.
Authors: Bouteska, Ahmed1, ahmedcbouteska@gmail.com, Seranto, Marco Lavazza2, marcolaser@gmail.com, Hajek, Petr3, petr.hajek@upce.cz, Abedin, Mohammad Zoynul4, m.z.abedin@swansea.ac.uk
Source: Annals of Operations Research; Dec2025, Vol. 355 Issue 2, p1587-1605, 19p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 190357746
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Data-driven decadal climate forecasting using Wasserstein time-series generative adversarial networks.
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  Data: <searchLink fieldCode="AU" term="%22Bouteska%2C+Ahmed%22">Bouteska, Ahmed</searchLink><relatesTo>1</relatesTo>, <i>ahmedcbouteska@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Seranto%2C+Marco+Lavazza%22">Seranto, Marco Lavazza</searchLink><relatesTo>2</relatesTo>, <i>marcolaser@gmail.com</i><br /><searchLink fieldCode="AU" term="%22Hajek%2C+Petr%22">Hajek, Petr</searchLink><relatesTo>3</relatesTo>, <i>petr.hajek@upce.cz</i><br /><searchLink fieldCode="AU" term="%22Abedin%2C+Mohammad+Zoynul%22">Abedin, Mohammad Zoynul</searchLink><relatesTo>4</relatesTo>, <i>m.z.abedin@swansea.ac.uk</i>
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  Data: <searchLink fieldCode="JN" term="%22Annals+of+Operations+Research%22">Annals of Operations Research</searchLink>; Dec2025, Vol. 355 Issue 2, p1587-1605, 19p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=190357746
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        Value: 10.1007/s10479-023-05722-7
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      – Code: eng
        Text: English
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              Text: Dec2025
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              Y: 2025
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