Local energy loss is among the essential parameters of culvert design, in which uncertainty and nonlinearity is controversial. In the present study, seven models were developed with the aid of the experimental data of slope-tapered culverts, and the efficiency of gene expression programing and Gaussian process regression as a kernel-based approach was assessed in predicting the entrance loss coefficient of a slope-tapered culvert. Also, one-at-a-time (OAT) sensitivity analysis was performed to determine the impact of input parameters. The results of both GEP and GPR methods with the performance criteria of R = 0.847, DC = 0.777, RMSE = 0.2 and R = 0.76, DC = 0.718, RMSE = 0.25 showed that the model with input parameters of Froude number (Fr), ratio of headwater to culvert diameter (H_w/D) and ratio of reducer length to barrel length (L_r/L) is the superior model. Although the accuracy of GEP method was slightly higher than GPR, obtained results proved the capability of the applied methods (i.e., high correlation coefficient (R) and coefficient of determination R² (DC) and low RMSE). Furthermore, OAT sensitivity analysis revealed that Froude number has the most impact on local loss coefficient and could cause a significant increment in model efficiency.

局部能量损失是涵洞设计的基本参数之一，其中不确定性和非线性是有争议的。在本研究中，利用斜坡锥形涵洞的实验数据开发了七个模型，并评估了基因表达程序和高斯过程回归作为基于核的方法在预测斜坡入口损失系数方面的效率。锥形涵洞。此外，还进行了一次（OAT）敏感性分析，以确定输入参数的影响。GEP和GPR方法的性能标准分别为R = 0.847，DC = 0.777，RMSE = 0.2和R = 0.76，DC = 0.718，RMSE = 0.25的结果表明，输入参数为Froude数（Fr）的模型，源水与涵洞直径之比（H _w/ D）和减速器长度与机筒长度的比率（L _r / L）是上乘模型。尽管GEP方法的准确性略高于GPR，但获得的结果证明了所应用方法的能力（即高相关系数（R）和测定系数R ²（DC）和低RMSE）。此外，OAT敏感性分析显示，弗洛德数对局部损耗系数影响最大，并且可能导致模型效率显着提高。