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Improving semi-empirical equations of ultimate bearing capacity of shallow foundations using soft computing polynomials

机译:使用软计算多项式改进浅层基础极限承载力的半经验方程

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This study presents the ultimate bearing capacity of shallow foundations in meaningful ways and improves its semi-empirical equations accordingly. Approaches including weighted genetic programming (WGP) and soft computing polynomials (SCP) are utilized to provide accurate prediction and visible formulas/polynomials for the ultimate bearing capacity. Visible formulas facilitate parameter studies, sensitivity analysis, and applications of pruning techniques. Analytical results demonstrate that the proposed SCP is outstanding in both prediction accuracy and provides simple polynomials as well. Notably, the SCP identifies that the shearing resistance angle and foundation geometry impact on improving the Vesic's semi-empirical equations.
机译:这项研究以有意义的方式介绍了浅层基础的极限承载力,并相应地改善了其半经验方程。利用包括加权遗传规划(WGP)和软计算多项式(SCP)在内的方法来提供准确的预测和可视的公式/多项式,以实现极限承载力。可见的公式有助于进行参数研究,敏感性分析和修剪技术的应用。分析结果表明,所提出的SCP在预测精度上都非常出色,并且还提供了简单的多项式。 SCP特别指出,抗剪角和基础几何形状对改善Vesic的半经验方程式有影响。

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