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Forecasting scope creep in Egyptian construction projects: an evaluation using Artificial Neural Network (ANN) and Random Forest models.

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Title: Forecasting scope creep in Egyptian construction projects: an evaluation using Artificial Neural Network (ANN) and Random Forest models.
Authors: ElAlem, Mahmoud Ahdy1 (AUTHOR) mahmoud.ahdy@gmail.com, Mahdi, Ibrahim Mahmoud2 (AUTHOR), Mohamadien, Hassan A.1 (AUTHOR), Hosny, Sally1 (AUTHOR)
Source: International Journal of Construction Management. Dec2025, Vol. 25 Issue 16, p2082-2101. 20p.
Database: Business Source Ultimate
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DbLabel: Business Source Ultimate
An: 189650896
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  Data: Forecasting scope creep in Egyptian construction projects: an evaluation using Artificial Neural Network (ANN) and Random Forest models.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Construction+Management%22">International Journal of Construction Management</searchLink>. Dec2025, Vol. 25 Issue 16, p2082-2101. 20p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=189650896
RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/15623599.2025.2502788
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      – Code: eng
        Text: English
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        PageCount: 20
        StartPage: 2082
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      – TitleFull: Forecasting scope creep in Egyptian construction projects: an evaluation using Artificial Neural Network (ANN) and Random Forest models.
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            NameFull: ElAlem, Mahmoud Ahdy
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            NameFull: Mahdi, Ibrahim Mahmoud
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            NameFull: Mohamadien, Hassan A.
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            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
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              Value: 25
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              Value: 16
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