A new method for parameter rate determination of nonlinear Mastingen model based on PSO

In view of the problems of linearization, complex solution and poor accuracy in the parameter rate determination of the Mastingen flood evolution model, a new method for parameterization of the Mastingen model based on the Particle Swarm Optimization (PSO) algorithm is proposed, and it is applied to the calculation of flood evolution in the Hook Bend-Linqing section. Through the comparative analysis with the PSO linear model and the least squares linear model parametric rate determination flood calculus, it is found that the accuracy of the nonlinear model based on PSO algorithm is higher than that of the two linear models, and the sum of the squared errors of the three typical floods in 1960, 1961 and 1964 is reduced by 0.9%, 6.2% and 1.6%, respectively, indicating that the parameter rate determination results of the nonlinear Mastingen model based on PSO are closer to the evolution process of actual floods.