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THE EVOLUTION OF RENEWABLE ENERGY FORECASTING WITH MACHINE LEARNING: A STATE-OF-THE-ART BIBLIOMETRIC ANALYSIS AND SUGGESTIONS FOR FUTURE RESEARCH.

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Title: THE EVOLUTION OF RENEWABLE ENERGY FORECASTING WITH MACHINE LEARNING: A STATE-OF-THE-ART BIBLIOMETRIC ANALYSIS AND SUGGESTIONS FOR FUTURE RESEARCH.
Authors: HAU, Y. S.1, KIM, E. M.2 keunmi100@pusan.ac.kr
Source: Applied Ecology & Environmental Research. 2025, Vol. 23 Issue 5, p8913-8939. 27p.
Database: Environment Complete
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Header DbId: eih
DbLabel: Environment Complete
An: 189071414
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: THE EVOLUTION OF RENEWABLE ENERGY FORECASTING WITH MACHINE LEARNING: A STATE-OF-THE-ART BIBLIOMETRIC ANALYSIS AND SUGGESTIONS FOR FUTURE RESEARCH.
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  Data: <searchLink fieldCode="AR" term="%22HAU%2C+Y%2E+S%2E%22">HAU, Y. S.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22KIM%2C+E%2E+M%2E%22">KIM, E. M.</searchLink><relatesTo>2</relatesTo><i> keunmi100@pusan.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22Applied+Ecology+%26+Environmental+Research%22">Applied Ecology & Environmental Research</searchLink>. 2025, Vol. 23 Issue 5, p8913-8939. 27p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eih&AN=189071414
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      – Type: doi
        Value: 10.15666/aeer/2305_89138939
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      – Code: eng
        Text: English
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        PageCount: 27
        StartPage: 8913
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      – TitleFull: THE EVOLUTION OF RENEWABLE ENERGY FORECASTING WITH MACHINE LEARNING: A STATE-OF-THE-ART BIBLIOMETRIC ANALYSIS AND SUGGESTIONS FOR FUTURE RESEARCH.
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            NameFull: HAU, Y. S.
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              Text: 2025
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              Y: 2025
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              Value: 23
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            – TitleFull: Applied Ecology & Environmental Research
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