Distribution of sediment concentration in open-channel flows, particularly in rivers, is one of the most important factors in understanding the river behavior, water quality, and design of hydraulic structures. Therefore, to determine the amount of transported suspended sediment, the sediment concentration distribution must be measured with high accuracy. In the present study, four intelligent methods of ANFIS-PSO, ANFIS-GA, ANFIS, and GMDH were used to predict the sediment concentration distribution. Since both GA and PSO optimization methods were used to optimize the ANFIS model, the performance of these models was significantly improved and their accuracies were increased. The results showed that the methods of ANFIS-PSO, ANFIS-GA, ANFIS, and GMDH were, respectively, the most accurate methods for prediction of suspended sediment distribution. Based on the evaluation of these methods, it was concluded that intelligent methods have considerable accuracy in predicting parameters affecting the suspended sediment distribution. Accordingly, considering the performance of these methods, a combination of optimization and intelligent methods may be useful for predicting sediment concentration distribution. It was also found that the ANFIS-PSO method can be a more appropriate and accurate method than other methods.

明渠流中泥沙浓度的分布，特别是在河流中，是了解河流行为、水质和水工结构设计的最重要因素之一。因此，要确定输送的悬浮泥沙量，必须高精度地测量泥沙浓度分布。本研究采用ANFIS-PSO、ANFIS-GA、ANFIS和GMDH四种智能方法预测含沙量分布。由于同时使用GA和PSO优化方法对ANFIS模型进行优化，这些模型的性能得到显着提高，精度也得到了提高。结果表明，ANFIS-PSO、ANFIS-GA、ANFIS和GMDH方法分别是预测悬浮泥沙分布最准确的方法。基于对这些方法的评估，可以得出结论，智能方法在预测影响悬浮泥沙分布的参数方面具有相当高的准确性。因此，考虑到这些方法的性能，优化和智能方法的组合可能有助于预测泥沙浓度分布。还发现ANFIS-PSO方法可以是比其他方法更合适和准确的方法。