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Updated: May 6, 2026

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先进的机器学习模型用于从奈和班加罗尔岩石样本的点负载强度指数预测不受限制的压力强度

Sowmya Kochukrishnan1, Premalatha Krishnamurthy2, Chintaluri Venkata Prasad3

  • 1Department of Civil Engineering, Anna University, Chennai, Tamil Nadu, India. sowmya.civil@gmail.com.

Scientific reports
|October 21, 2025
PubMed
概括

点负荷测试 (PLI) 准确地预测了岩石不受限制的压力 (UCS). 轴向PLI显示出比直径PLI (R2=0.991) 更强的相关性 (R2=0.996),神经网络和高斯过程回归模型表现最好.

关键词:
班加罗尔的摇滚岩石.奈摇滚的摇滚的摇滚.机器学习模型的机器学习模型时间点负载指数指数.回归学习应用程序回归学习应用程序没有限制的压力强度.

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