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Knowledge-Based XGBoost Model for Predicting Corrosion-Fatigue Crack Growth Rate in Aluminum Alloys.

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Title: Knowledge-Based XGBoost Model for Predicting Corrosion-Fatigue Crack Growth Rate in Aluminum Alloys.
Authors: Wang, Peng1,2, wang_peng@cgnpc.com.cn, Chen, Xin1,2, Zhang, Yongzhen3
Source: Crystals (2073-4352); Apr2026, Vol. 16 Issue 4, p273, 17p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 193440046
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  Data: Knowledge-Based XGBoost Model for Predicting Corrosion-Fatigue Crack Growth Rate in Aluminum Alloys.
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  Data: <searchLink fieldCode="AU" term="%22Wang%2C+Peng%22">Wang, Peng</searchLink><relatesTo>1,2</relatesTo>, <i>wang_peng@cgnpc.com.cn</i><br /><searchLink fieldCode="AU" term="%22Chen%2C+Xin%22">Chen, Xin</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AU" term="%22Zhang%2C+Yongzhen%22">Zhang, Yongzhen</searchLink><relatesTo>3</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Crystals+%282073-4352%29%22">Crystals (2073-4352)</searchLink>; Apr2026, Vol. 16 Issue 4, p273, 17p
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    Identifiers:
      – Type: doi
        Value: 10.3390/cryst16040273
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      – Code: eng
        Text: English
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        PageCount: 17
        StartPage: 273
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      – TitleFull: Knowledge-Based XGBoost Model for Predicting Corrosion-Fatigue Crack Growth Rate in Aluminum Alloys.
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            NameFull: Wang, Peng
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            NameFull: Chen, Xin
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            NameFull: Zhang, Yongzhen
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            – D: 01
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              Text: Apr2026
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              Y: 2026
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              Value: 16
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