Optimization estimation of Muskingum model parameter based on genetic algorithm

Abstract

Trial-and-error method used in ascertaining the model parameters of Muskingum can not get the optimal solution usually, and the calculation is very complex. The calculation precision of other methods, such as non-linear programming and least square method, is also not ideal. To solve this problem, genetic algorithm, which has global optimization ability, is applied to solve the Muskingum model parameters. Study case shows that computation precision of genetic algorithm has obvious advantages compared with traditional methods. © 2012 Springer-Verlag GmbH.