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Optimization of Earth Dam Cross-Sections Using the Max–Min Ant System and Artificial Neural Networks with Real Case Studies.

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Title: Optimization of Earth Dam Cross-Sections Using the Max–Min Ant System and Artificial Neural Networks with Real Case Studies.
Authors: Rezaeian, Amin1, Davoodi, Mohammad2, Jafari, Mohammad Kazem2,3, Bagheri, Mohsen3,4, Asgari, Ali4,5, a.asgari@umz.ac.ir, Jafarian Kafshgarkolaei, Hassan1,5
Source: Buildings (2075-5309); Feb2026, Vol. 16 Issue 3, p501, 22p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 191609087
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PubType: Academic Journal
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  Data: Optimization of Earth Dam Cross-Sections Using the Max–Min Ant System and Artificial Neural Networks with Real Case Studies.
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  Data: <searchLink fieldCode="JN" term="%22Buildings+%282075-5309%29%22">Buildings (2075-5309)</searchLink>; Feb2026, Vol. 16 Issue 3, p501, 22p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=191609087
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      – Type: doi
        Value: 10.3390/buildings16030501
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      – Code: eng
        Text: English
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        PageCount: 22
        StartPage: 501
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      – TitleFull: Optimization of Earth Dam Cross-Sections Using the Max–Min Ant System and Artificial Neural Networks with Real Case Studies.
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            NameFull: Rezaeian, Amin
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            NameFull: Davoodi, Mohammad
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              Text: Feb2026
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              Y: 2026
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