In irrigation and drainage structures, side weir is widely used for flow diversion from main to branch channels. Side weir is also used as a measuring device for discharge measurements, so discharge coefficient was mainly studied in many previous studies. Skew side weir was not taking a good highlight in previous studies and literature, so the present work discharge coefficient calculation for the skew side weir was adopted and studied. Multiple Linear Regression (MLR) and Gene Expression Programming (GEP) tools were used in the present study and compared with observed values of C_d. The mean absolute error for C_d observed and calculated in MLR and GEP was not exceeded 5%. The C_d values for skew side weir ranged from (0.65) to (0.85), while its values for straight vertical side from previous literature weir ranged from (0.45) to (0.65); this mean skew side weir can be used for increase in discharge diversion to the branch channel at the same water levels by 27%. The Akaike information criteria (AIC) with (AICs), root-mean-square error (RMSE), mean absolute relative error (MARE) and scatter index (SI) are used in this study for measuring the GEP model performance. From results, the GEP model has AIC = − 216.51, AICs = − 918.51, RMSE = 0.004653, MARE = 0.005234, R² = 0.994 and SI = 0.006231 performed the best. According to previous results, the new equation presented through GEP can be adopted for discharge coefficient calculation in skew side weir.

中文翻译：

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基因表达程序设计（GEP）预测倾斜侧堰的排放系数

在排灌结构中，侧堰被广泛用于从主水道到支水道的分流。侧堰也用作放电测量的测量装置，因此在许多先前的研究中主要研究了放电系数。在以往的研究和文献中，偏侧堰没有得到很好的重视，因此采用和研究了目前偏侧堰的工作流量系数计算方法。本研究使用多元线性回归（MLR）和基因表达编程（GEP）工具，并将其与C _d的观测值进行比较。在MLR和GEP中观察和计算的C _d的平均绝对误差不超过5％。在C ^ _d偏侧堰的值在（0.65）至（0.85）之间，而先前文献堰的直垂直堰的值在（0.45）至（0.65）之间；在相同的水位下，该平均偏斜侧堰可用于将排放转移到支路的流量增加27％。这项研究使用Akaike信息标准（AIC），（AIC），均方根误差（RMSE），平均绝对相对误差（MARE）和分散指数（SI）来衡量GEP模型的性能。从结果来看，GEP模型的AIC =-216.51，AICs =-918.51，RMSE = 0.004653，MARE = 0.005234，R ²  = 0.994和SI = 0.006231表现最佳。根据先前的结果，可以将通过GEP提出的新方程式用于偏侧堰的排水系数计算。