A complete set of 13 morphological parameters in accordance with standard ISO 4287 was applied to quantifying a series of random profiles. These profiles were imported into a discrete numerical model to perform 480 interface shear tests on coarse-grained soils. The relevant morphological parameters were selected using Spearman’s rank correlation coefficient for model selection. An optimal metaheuristic model was developed using a genetic algorithm and was further compared with the existing predicted formulas. The 2D discrete element method (DEM) results indicate that the highest correlation with shear strength was obtained for the hybrid parameter Pdq which represents not only the amplitude information but also the surface slope information on a random surface. The optimal model with one significant input variable ($\mathit{Pdq}$) was effectively selected through the Bayesian nonparametric general regression analysis. For irregular interface shearing widely existing in most geotechnical engineering, $\mathit{Pdq}$ is more efficient and accurate to quantify the surface morphology or estimate the interface shear strength compared with relative roughness.

根据标准ISO 4287的一整套13个形态学参数被用于量化一系列随机轮廓。将这些剖面导入到离散数值模型中，以在粗粒土上执行480个界面剪切测试。使用Spearman秩相关系数选择相关的形态学参数进行模型选择。使用遗传算法开发了最佳的元启发式模型，并将其与现有的预测公式进行了进一步的比较。二维离散元方法（DEM）结果表明，混合参数Pdq与剪切强度具有最高相关性它不仅表示振幅信息，而且还表示随机表面上的表面坡度信息。具有一个重要输入变量的最优模型（$\mathit{Pdq}$）是通过贝叶斯非参数一般回归分析有效选择的。对于大多数岩土工程中广泛存在的不规则界面剪切，$\mathit{Pdq}$ 与相对粗糙度相比，它更有效，更准确地量化了表面形态或估计了界面剪切强度。