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Interpolation and Machine Learning Methods for Sub-Hourly Missing Rainfall Data Imputation in a Data-Scarce Environment: One- and Two-Step Approaches.

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Title: Interpolation and Machine Learning Methods for Sub-Hourly Missing Rainfall Data Imputation in a Data-Scarce Environment: One- and Two-Step Approaches.
Authors: Boukdire, Mohamed1 (AUTHOR), İnan, Çağrı Alperen2 (AUTHOR), Varra, Giada3 (AUTHOR), Della Morte, Renata1,3 (AUTHOR) renata.dellamorte@uniparthenope.it, Cozzolino, Luca2,3 (AUTHOR)
Source: Hydrology (2306-5338). Nov2025, Vol. 12 Issue 11, p297. 27p.
Database: Environment Complete
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eih&AN=189652984
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      – Type: doi
        Value: 10.3390/hydrology12110297
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 27
        StartPage: 297
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      – TitleFull: Interpolation and Machine Learning Methods for Sub-Hourly Missing Rainfall Data Imputation in a Data-Scarce Environment: One- and Two-Step Approaches.
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            NameFull: Boukdire, Mohamed
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            NameFull: İnan, Çağrı Alperen
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            NameFull: Varra, Giada
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            NameFull: Della Morte, Renata
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            – D: 01
              M: 11
              Text: Nov2025
              Type: published
              Y: 2025
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              Value: 12
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              Value: 11
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