Parameters identification of groundwater flow model with genetic algorithm and Gauss-Newton Method

With genetic algorithm (GA) regard to nonlinear optimization problems, has a good capability of searching in the whole solving space. But in the part of solving space, GA has a low capability of searching and gives a low precision of solution. As for Gauss-Newton Method (GNM) nonlinear optimization problems, has inverse characters opposite from GA. The strongpoint of GA and GNM were full used in parameters identification of ground water flow numerical model. At first, GA solved the initial values of parameter. Then, the parameters were identified by GNM with the initial values of parameter. A 2-Dimensional unsteady flows in an inhomogeneous, isotropic confined aquifer for an ideal model was employed, and the application of GA and GNM to inverse problems of hydrogeology parameters with finite element method was discussed. It is shown by the calculated results that the algorithm has several main functions, such as expediting constringency, and improving precision.