001037649 001__ 1037649
001037649 005__ 20250203124520.0
001037649 0247_ $$2doi$$a10.1016/j.energy.2023.128068
001037649 0247_ $$2ISSN$$a0360-5442
001037649 0247_ $$2ISSN$$a1873-6785
001037649 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-00814
001037649 0247_ $$2WOS$$aWOS:001025860900001
001037649 037__ $$aFZJ-2025-00814
001037649 082__ $$a600
001037649 1001_ $$00000-0003-2860-1441$$aShin, Heesoo$$b0
001037649 245__ $$aEffects of spatiotemporal correlations in wind data on neural network-based wind predictions
001037649 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2023
001037649 3367_ $$2DRIVER$$aarticle
001037649 3367_ $$2DataCite$$aOutput Types/Journal article
001037649 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1737442900_21957
001037649 3367_ $$2BibTeX$$aARTICLE
001037649 3367_ $$2ORCID$$aJOURNAL_ARTICLE
001037649 3367_ $$00$$2EndNote$$aJournal Article
001037649 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001037649 536__ $$0G:(EU-Grant)951733$$aRAISE - Research on AI- and Simulation-Based Engineering at Exascale (951733)$$c951733$$fH2020-INFRAEDI-2019-1$$x1
001037649 536__ $$0G:(DE-Juel1)HDS-LEE-20190612$$aHDS LEE - Helmholtz School for Data Science in Life, Earth and Energy (HDS LEE) (HDS-LEE-20190612)$$cHDS-LEE-20190612$$x2
001037649 588__ $$aDataset connected to CrossRef, Journals: juser.fz-juelich.de
001037649 7001_ $$0P:(DE-Juel1)177985$$aRüttgers, Mario$$b1
001037649 7001_ $$00000-0001-7341-8289$$aLee, Sangseung$$b2$$eCorresponding author
001037649 773__ $$0PERI:(DE-600)2019804-8$$a10.1016/j.energy.2023.128068$$gVol. 279, p. 128068 -$$p128068$$tEnergy$$v279$$x0360-5442$$y2023
001037649 8564_ $$uhttps://juser.fz-juelich.de/record/1037649/files/2304.01545v4.pdf$$yOpenAccess
001037649 909CO $$ooai:juser.fz-juelich.de:1037649$$pdnbdelivery$$pec_fundedresources$$pVDB$$pdriver$$popen_access$$popenaire
001037649 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)177985$$aForschungszentrum Jülich$$b1$$kFZJ
001037649 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001037649 9141_ $$y2024
001037649 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)1160$$2StatID$$aDBCoverage$$bCurrent Contents - Engineering, Computing and Technology$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bENERGY : 2022$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001037649 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)9905$$2StatID$$aIF >= 5$$bENERGY : 2022$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2025-01-02
001037649 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2025-01-02$$wger
001037649 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2025-01-02
001037649 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
001037649 9801_ $$aFullTexts
001037649 980__ $$ajournal
001037649 980__ $$aVDB
001037649 980__ $$aUNRESTRICTED
001037649 980__ $$aI:(DE-Juel1)JSC-20090406