Genetic algorithm-based intelligent inverse model for identification of channel network roughness

Estimation of roughness parameters is a crucial technique in channel network flow simulation. An intelligent inverse model for identifying channel network roughness parameters was developed based on the Genetic algorithm and the channel network hydrodynamic model. The model was used to determine the roughness parameters of the channel network in Hangjiang Delta. Sound agreement is obtained between the calculated and observed results. The results show that the model has a higher accuracy and a quicker convergent speed. It provides a good technique for identifying parameters of mathematical model.