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Updated: May 26, 2025

Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation
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Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation

Published on: November 18, 2015

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用先进的机器学习组合来评估地质物理流预测的斜率行为.

Kennedy C Onyelowe1,2, Ahmed M Ebid3, Shadi Hanandeh4

  • 1Department of Civil Engineering, Michael Okpara University of Agriculture, Umudike, 440109, Nigeria. kennedychibuzor@kiu.ac.ug.

Scientific reports
|February 23, 2025
PubMed
概括

这项研究使用软计算增强了斜率稳定性分析,人工神经网络 (ANN) 在预测安全因子 (FOS) 中超过了其他模型. 数据处理的组方法 (GMDH) 通过其用于手动应用的闭式方程提供了实际优势.

关键词:
一个年龄,一个年龄.先进的机器学习技术.安全的安全因素.地理危险 危险地质地质物理流的流动斜坡的稳定性 斜坡的稳定性

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