Simulation of Flood Water Level Using PSO-Based RBF Neural Network

The flood water level forecasting is an important work for flood decision-making. The determination of flood water level is the key for the numerical simulation of river channel. There are many factors influencing flood water level, therefore, it is difficult to get the accurate value. After analyzing the factors influencing flood water level, a PSO-based RBF neural network model is set up to calculate the flood water level. Through the verification of the roughness coefficient at lower yellow river, the results show that the neural network model can calculate roughness coefficient accurately.