The current study introduces a novel approach to estimate the incipient motion of sediments under a wide range of flow regimes by developing a fuzzy model with a fuzzy-band that refers to a transition from weak motion to general motion of sediment. The partial sediment entrainment is defined by fuzzy sets considering the uncertainty related to the individual ratio of inertia to viscous forces which is the definition of shear Reynolds number. In the current study, the Mamdani Fuzzy Inference System (Mamdani FIS) is used to develop a comprehensive fuzzy model of the incipient motion of sediment. The Mamdani FIS has a shortcoming regarding the training of the fuzzy model. To estimate the dimensionless shear stress, a new method is developed by combining a genetic algorithm with the fuzzy approach which is named the Geno-Mamdani Fuzzy Inference System (GMFIS) method. The performance of the GMFIS model is evaluated using experimental data by considering root mean square error (RMSE), Nash-Sutcliffe coefficient of efficiency (CE), degree of robustness (D_r), and concordance coefficient (CC) as evaluation criteria. The GMFIS model performed very well based on the RMSE, CE, D_r, and CC values and satisfactorily represented the three types of incipient motion. Finally, a new range of fuzzy, dimensionless, critical shear stress values is established in all flow conditions from weak to general sediment entrainment.

当前的研究介绍了一种新颖的方法，通过开发带有模糊带的模糊模型来估计在宽范围的流态下的沉积物的初始运动，该模糊模型是指从弱运动到沉积物的一般运动的过渡。考虑到与单个惯性与粘性力之比有关的不确定性（即剪切雷诺数的定义），通过模糊集来定义部分沉积物夹带。在当前的研究中，Mamdani模糊推理系统（Mamdani FIS）用于开发泥沙早期运动的综合模糊模型。Mamdani FIS在训练模糊模型方面有一个缺点。要估算无因次剪应力，通过将遗传算法与模糊方法相结合，开发出一种新的方法，称为Geno-Mamdani模糊推理系统（GMFIS）方法。使用实验数据通过考虑均方根误差（RMSE），Nash-Sutcliffe效率系数（CE），鲁棒程度（D）来评估GMFIS模型的性能_r），以及一致性系数（CC）作为评估标准。该GMFIS模型表现非常出色基于所述RMSE，CE，d _{- [R} ，和CC值并令人满意地表示的三种类型的初始运动。最后，在从弱到一般的泥沙夹带的所有流动条件下，建立了一个新的模糊，无量纲，临界剪应力值范围。