Enhanced Water Quality Prediction in the Yellow River Basin: Application of the SSA-RBF Model

Abstract

Watershed water quality monitoring is of great significance in water environment protection and management, and this paper proposes a water quality prediction model based on RBF neural network. Aiming at the parameter optimisation of RBF water quality prediction model, we propose to apply the sparrow search algorithm to optimise the parameters of the RBF model, aiming to improve the global search ability and convergence speed of the model. The characteristics of water quality parameters in the Shaanxi section of the Yellow River Basin were analysed using the model. Comparison with the RBF prediction algorithm is made, and the SSA-RBF prediction algorithm can significantly improve the prediction performance of the RBF model.