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Integrating Drilling Parameters and Face Images for Tunnel Rock Mass Classification Using a Hybrid Random Forest and MambaVision Model.

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Title: Integrating Drilling Parameters and Face Images for Tunnel Rock Mass Classification Using a Hybrid Random Forest and MambaVision Model.
Authors: Yang, Peng1, Zhao, Qiang1,2, Zhang, Bentie1,3, Zhou, Dong1,2, Lv, Lu2,3, lyulu0603@xauat.edu.cn
Source: Buildings (2075-5309); May2026, Vol. 16 Issue 10, p1916, 24p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
An: 194142629
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Integrating Drilling Parameters and Face Images for Tunnel Rock Mass Classification Using a Hybrid Random Forest and MambaVision Model.
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      – Type: doi
        Value: 10.3390/buildings16101916
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      – Code: eng
        Text: English
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        PageCount: 24
        StartPage: 1916
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      – TitleFull: Integrating Drilling Parameters and Face Images for Tunnel Rock Mass Classification Using a Hybrid Random Forest and MambaVision Model.
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            NameFull: Yang, Peng
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            NameFull: Zhao, Qiang
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            NameFull: Zhang, Bentie
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              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 16
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