Suspended Sediment Load Prediction Using Sparrow Search Algorithm-based Support Vector Machine Model

In this article, the authors propose a robust model, SVM-SSA, for predicting suspended sediment load in streams using support vector machine and a novel sparrow search algorithm. The model is compared to three other hybrid models and a benchmark SVM model, and it is found to have the highest accuracy. The results suggest that this approach is suitable for accurately predicting sediment load in rivers.